151
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Girdhar K, Bendl J, Baumgartner A, Therrien K, Venkatesh S, Mathur D, Dong P, Rahman S, Kleopoulos SP, Misir R, Reach SM, Auluck PK, Marenco S, Lewis DA, Haroutunian V, Funk C, Voloudakis G, Hoffman GE, Fullard JF, Roussos P. The neuronal chromatin landscape in adult schizophrenia brains is linked to early fetal development. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.02.23296067. [PMID: 37873320 PMCID: PMC10593028 DOI: 10.1101/2023.10.02.23296067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Non-coding variants increase risk of neuropsychiatric disease. However, our understanding of the cell-type specific role of the non-coding genome in disease is incomplete. We performed population scale (N=1,393) chromatin accessibility profiling of neurons and non-neurons from two neocortical brain regions: the anterior cingulate cortex and dorsolateral prefrontal cortex. Across both regions, we observed notable differences in neuronal chromatin accessibility between schizophrenia cases and controls. A per-sample disease pseudotime was positively associated with genetic liability for schizophrenia. Organizing chromatin into cis- and trans-regulatory domains, identified a prominent neuronal trans-regulatory domain (TRD1) active in immature glutamatergic neurons during fetal development. Polygenic risk score analysis using genetic variants within chromatin accessibility of TRD1 successfully predicted susceptibility to schizophrenia in the Million Veteran Program cohort. Overall, we present the most extensive resource to date of chromatin accessibility in the human cortex, yielding insights into the cell-type specific etiology of schizophrenia.
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Affiliation(s)
- Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Karen Therrien
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Sanan Venkatesh
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Deepika Mathur
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Pengfei Dong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Samir Rahman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Steven P Kleopoulos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ruth Misir
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sarah M Reach
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Pavan K Auluck
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
| | - Stefano Marenco
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
| | - David A Lewis
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Vahram Haroutunian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Cory Funk
- Institute for Systems Biology, Seattle, WA, 98109, USA
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
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152
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Girdhar K, Bendl J, Baumgartner A, Therrien K, Venkatesh S, Mathur D, Dong P, Rahman S, Kleopoulos SP, Misir R, Reach SM, Auluck PK, Marenco S, Lewis DA, Haroutunian V, Funk C, Voloudakis G, Hoffman GE, Fullard JF, Roussos P. The neuronal chromatin landscape in adult schizophrenia brains is linked to early fetal development. RESEARCH SQUARE 2023:rs.3.rs-3393581. [PMID: 37886514 PMCID: PMC10602154 DOI: 10.21203/rs.3.rs-3393581/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Non-coding variants increase risk of neuropsychiatric disease. However, our understanding of the cell-type specific role of the non-coding genome in disease is incomplete. We performed population scale (N=1,393) chromatin accessibility profiling of neurons and non-neurons from two neocortical brain regions: the anterior cingulate cortex and dorsolateral prefrontal cortex. Across both regions, we observed notable differences in neuronal chromatin accessibility between schizophrenia cases and controls. A per-sample disease pseudotime was positively associated with genetic liability for schizophrenia. Organizing chromatin into cis- and trans-regulatory domains, identified a prominent neuronal trans-regulatory domain (TRD1) active in immature glutamatergic neurons during fetal development. Polygenic risk score analysis using genetic variants within chromatin accessibility of TRD1 successfully predicted susceptibility to schizophrenia in the Million Veteran Program cohort. Overall, we present the most extensive resource to date of chromatin accessibility in the human cortex, yielding insights into the cell-type specific etiology of schizophrenia.
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Affiliation(s)
- Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Karen Therrien
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Sanan Venkatesh
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Deepika Mathur
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Pengfei Dong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Samir Rahman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Steven P Kleopoulos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ruth Misir
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sarah M Reach
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Pavan K Auluck
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
| | - Stefano Marenco
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
| | - David A Lewis
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Vahram Haroutunian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Cory Funk
- Institute for Systems Biology, Seattle, WA, 98109, USA
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
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153
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Jani C, Marsh A, Uchil P, Jain N, Baskir ZR, Glover OT, Root DE, Doench JG, Barczak AK. Vps18 contributes to phagosome membrane integrity in Mycobacterium tuberculosis-infected macrophages. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.01.560397. [PMID: 37873319 PMCID: PMC10592876 DOI: 10.1101/2023.10.01.560397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Mycobacterium tuberculosis (Mtb) has evolved to be exquisitely adapted to survive within host macrophages. The capacity to damage the phagosomal membrane has emerged as central to Mtb virulence. While Mtb factors driving membrane damage have been described, host factors that repair that damage to contain the pathogen remain largely unknown. We used a genome-wide CRISPR screen to identify novel host factors required to repair Mtb-damaged phagosomal membranes. Vacuolar protein sorting-associated protein 18 (Vps18), a member of the HOPS and CORVET trafficking complexes, was among the top hits. Vps18 colocalized with Mtb in macrophages beginning shortly after infection, and Vps18-knockout macrophages demonstrated increased damage of Mtb-containing phagosomes without impaired autophagy. Mtb grew more robustly in Vps18-knockout cells, and the first-line anti-tuberculosis antibiotic pyrazinamide was less effective. Our results identify Vps18 as required for phagosomal membrane integrity in Mtb-infected cells and suggest that modulating phagosome integrity may hold promise for improving the efficacy of antibiotic treatment for TB.
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Affiliation(s)
| | | | - Pooja Uchil
- The Ragon Institute of MGH, MIT and Harvard
- Institute of Clinical and Molecular Virology, Friedrich-Alexander Universität Erlangen-Nürnberg
| | - Neha Jain
- The Ragon Institute of MGH, MIT and Harvard
| | | | | | | | | | - Amy K Barczak
- The Ragon Institute of MGH, MIT and Harvard
- The Broad Institute
- Division of Infectious Diseases, Massachusetts General Hospital
- Department of Medicine, Harvard Medical School
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154
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Hou L, Xiong X, Park Y, Boix C, James B, Sun N, He L, Patel A, Zhang Z, Molinie B, Van Wittenberghe N, Steelman S, Nusbaum C, Aguet F, Ardlie KG, Kellis M. Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease. Nat Genet 2023; 55:1665-1676. [PMID: 37770633 PMCID: PMC10562256 DOI: 10.1038/s41588-023-01509-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 08/22/2023] [Indexed: 09/30/2023]
Abstract
Genetic variants associated with complex traits are primarily noncoding, and their effects on gene-regulatory activity remain largely uncharacterized. To address this, we profile epigenomic variation of histone mark H3K27ac across 387 brain, heart, muscle and lung samples from Genotype-Tissue Expression (GTEx). We annotate 282 k active regulatory elements (AREs) with tissue-specific activity patterns. We identify 2,436 sex-biased AREs and 5,397 genetically influenced AREs associated with 130 k genetic variants (haQTLs) across tissues. We integrate genetic and epigenomic variation to provide mechanistic insights for disease-associated loci from 55 genome-wide association studies (GWAS), by revealing candidate tissues of action, driver SNPs and impacted AREs. Lastly, we build ARE-gene linking scores based on genetics (gLink scores) and demonstrate their unique ability to prioritize SNP-ARE-gene circuits. Overall, our epigenomic datasets, computational integration and mechanistic predictions provide valuable resources and important insights for understanding the molecular basis of human diseases/traits such as schizophrenia.
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Affiliation(s)
- Lei Hou
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Xushen Xiong
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Liangzhu Laboratory, Zhejiang University, Hangzhou, China
| | - Yongjin Park
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Carles Boix
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Benjamin James
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Na Sun
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Liang He
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Aman Patel
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Zhizhuo Zhang
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Benoit Molinie
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - Scott Steelman
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Chad Nusbaum
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - François Aguet
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - Manolis Kellis
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA.
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Kavousi M, Bos MM, Barnes HJ, Lino Cardenas CL, Wong D, Lu H, Hodonsky CJ, Landsmeer LPL, Turner AW, Kho M, Hasbani NR, de Vries PS, Bowden DW, Chopade S, Deelen J, Benavente ED, Guo X, Hofer E, Hwang SJ, Lutz SM, Lyytikäinen LP, Slenders L, Smith AV, Stanislawski MA, van Setten J, Wong Q, Yanek LR, Becker DM, Beekman M, Budoff MJ, Feitosa MF, Finan C, Hilliard AT, Kardia SLR, Kovacic JC, Kral BG, Langefeld CD, Launer LJ, Malik S, Hoesein FAAM, Mokry M, Schmidt R, Smith JA, Taylor KD, Terry JG, van der Grond J, van Meurs J, Vliegenthart R, Xu J, Young KA, Zilhão NR, Zweiker R, Assimes TL, Becker LC, Bos D, Carr JJ, Cupples LA, de Kleijn DPV, de Winther M, den Ruijter HM, Fornage M, Freedman BI, Gudnason V, Hingorani AD, Hokanson JE, Ikram MA, Išgum I, Jacobs DR, Kähönen M, Lange LA, Lehtimäki T, Pasterkamp G, Raitakari OT, Schmidt H, Slagboom PE, Uitterlinden AG, Vernooij MW, Bis JC, Franceschini N, Psaty BM, Post WS, Rotter JI, Björkegren JLM, O'Donnell CJ, Bielak LF, Peyser PA, Malhotra R, van der Laan SW, Miller CL. Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification. Nat Genet 2023; 55:1651-1664. [PMID: 37770635 PMCID: PMC10601987 DOI: 10.1038/s41588-023-01518-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 08/29/2023] [Indexed: 09/30/2023]
Abstract
Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.
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Affiliation(s)
- Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
| | - Maxime M Bos
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Hanna J Barnes
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Christian L Lino Cardenas
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Doris Wong
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Haojie Lu
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Chani J Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Lennart P L Landsmeer
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Adam W Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea
| | - Natalie R Hasbani
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Center at Houston, Houston, TX, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Center at Houston, Houston, TX, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Sandesh Chopade
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- University College London British Heart Foundation Research Accelerator Centre, London, UK
| | - Joris Deelen
- Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Max Planck Institute for Biology of Aging, Cologne, Germany
| | - Ernest Diez Benavente
- Laboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Edith Hofer
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University of Graz, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | | | - Sharon M Lutz
- Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Lotte Slenders
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Albert V Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Icelandic Heart Association, Kopavogur, Iceland
| | - Maggie A Stanislawski
- Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Jessica van Setten
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Quenna Wong
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Diane M Becker
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marian Beekman
- Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Matthew J Budoff
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Mary F Feitosa
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Chris Finan
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- University College London British Heart Foundation Research Accelerator Centre, London, UK
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | | | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jason C Kovacic
- Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia
- St Vincent's Clinical School, University of NSW, Sydney, New South Wales, Australia
- The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Brian G Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences and Data Science, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Shaista Malik
- Susan Samueli Integrative Health Institute, Department of Medicine, University of California Irvine, Irvine, CA, USA
| | | | - Michal Mokry
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Laboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University of Graz, Graz, Austria
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - James G Terry
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeroen van der Grond
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Joyce van Meurs
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jianzhao Xu
- Department of Biochemistry, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Kendra A Young
- Department of Epidemiology, University of Colorado, Anschutz Medical Campus, Denver, CO, USA
| | | | - Robert Zweiker
- Department of Internal Medicine, Division of Cardiology, Medical University of Graz, Graz, Austria
| | - Themistocles L Assimes
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Lewis C Becker
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Bos
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - J Jeffrey Carr
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - L Adrienne Cupples
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - Dominique P V de Kleijn
- Department of Vascular Surgery, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Menno de Winther
- Department of Medical Biochemistry, Experimental Vascular Biology, Amsterdam Cardiovascular Sciences: Atherosclerosis and Ischemic syndromes, Amsterdam Infection and Immunity: Inflammatory diseases, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Myriam Fornage
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Barry I Freedman
- Department of Internal Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, School of Public Health, University of Iceland, Reykjavik, Iceland
| | - Aroon D Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- University College London British Heart Foundation Research Accelerator Centre, London, UK
| | - John E Hokanson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ivana Išgum
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Leslie A Lange
- Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Helena Schmidt
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Medical University of Graz, Graz, Austria
| | - P Eline Slagboom
- Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Vascular Surgery, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Departments of Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Wendy S Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
- Department of Medicine, Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge, Sweden
| | - Christopher J O'Donnell
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Cardiology Section, Department of Medicine, Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Rajeev Malhotra
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Clint L Miller
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA.
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA.
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156
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Li W, Lu J, Lu P, Gao Y, Bai Y, Chen K, Su X, Li M, Liu J, Chen Y, Wen L, Tang F. scNanoHi-C: a single-cell long-read concatemer sequencing method to reveal high-order chromatin structures within individual cells. Nat Methods 2023; 20:1493-1505. [PMID: 37640936 DOI: 10.1038/s41592-023-01978-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 07/19/2023] [Indexed: 08/31/2023]
Abstract
The high-order three-dimensional (3D) organization of regulatory genomic elements provides a topological basis for gene regulation, but it remains unclear how multiple regulatory elements across the mammalian genome interact within an individual cell. To address this, herein, we developed scNanoHi-C, which applies Nanopore long-read sequencing to explore genome-wide proximal high-order chromatin contacts within individual cells. We show that scNanoHi-C can reliably and effectively profile 3D chromatin structures and distinguish structure subtypes among individual cells. This method could also be used to detect genomic variations, including copy-number variations and structural variations, as well as to scaffold the de novo assembly of single-cell genomes. Notably, our results suggest that extensive high-order chromatin structures exist in active chromatin regions across the genome, and multiway interactions between enhancers and their target promoters were systematically identified within individual cells. Altogether, scNanoHi-C offers new opportunities to investigate high-order 3D genome structures at the single-cell level.
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Affiliation(s)
- Wen Li
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Changping Laboratory, Beijing, China
| | - Jiansen Lu
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Changping Laboratory, Beijing, China
| | - Ping Lu
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Yun Gao
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Yichen Bai
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China
| | - Kexuan Chen
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Xinjie Su
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Mengyao Li
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China
| | - Jun'e Liu
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China
| | - Yijun Chen
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Lu Wen
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Fuchou Tang
- School of Life Sciences, Biomedical Pioneering Innovative Center, Peking University, Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China.
- Changping Laboratory, Beijing, China.
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157
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Malfait J, Wan J, Spicuglia S. Epromoters are new players in the regulatory landscape with potential pleiotropic roles. Bioessays 2023; 45:e2300012. [PMID: 37246247 DOI: 10.1002/bies.202300012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/11/2023] [Accepted: 05/15/2023] [Indexed: 05/30/2023]
Abstract
Precise spatiotemporal control of gene expression during normal development and cell differentiation is achieved by the combined action of proximal (promoters) and distal (enhancers) cis-regulatory elements. Recent studies have reported that a subset of promoters, termed Epromoters, works also as enhancers to regulate distal genes. This new paradigm opened novel questions regarding the complexity of our genome and raises the possibility that genetic variation within Epromoters has pleiotropic effects on various physiological and pathological traits by differentially impacting multiple proximal and distal genes. Here, we discuss the different observations pointing to an important role of Epromoters in the regulatory landscape and summarize the evidence supporting a pleiotropic impact of these elements in disease. We further hypothesize that Epromoter might represent a major contributor to phenotypic variation and disease.
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Affiliation(s)
- Juliette Malfait
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, LIGUE, Marseille, France
| | - Jing Wan
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, LIGUE, Marseille, France
| | - Salvatore Spicuglia
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, LIGUE, Marseille, France
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158
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Xiong X, James BT, Boix CA, Park YP, Galani K, Victor MB, Sun N, Hou L, Ho LL, Mantero J, Scannail AN, Dileep V, Dong W, Mathys H, Bennett DA, Tsai LH, Kellis M. Epigenomic dissection of Alzheimer's disease pinpoints causal variants and reveals epigenome erosion. Cell 2023; 186:4422-4437.e21. [PMID: 37774680 PMCID: PMC10782612 DOI: 10.1016/j.cell.2023.08.040] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 04/04/2023] [Accepted: 08/29/2023] [Indexed: 10/01/2023]
Abstract
Recent work has identified dozens of non-coding loci for Alzheimer's disease (AD) risk, but their mechanisms and AD transcriptional regulatory circuitry are poorly understood. Here, we profile epigenomic and transcriptomic landscapes of 850,000 nuclei from prefrontal cortexes of 92 individuals with and without AD to build a map of the brain regulome, including epigenomic profiles, transcriptional regulators, co-accessibility modules, and peak-to-gene links in a cell-type-specific manner. We develop methods for multimodal integration and detecting regulatory modules using peak-to-gene linking. We show AD risk loci are enriched in microglial enhancers and for specific TFs including SPI1, ELF2, and RUNX1. We detect 9,628 cell-type-specific ATAC-QTL loci, which we integrate alongside peak-to-gene links to prioritize AD variant regulatory circuits. We report differential accessibility of regulatory modules in late AD in glia and in early AD in neurons. Strikingly, late-stage AD brains show global epigenome dysregulation indicative of epigenome erosion and cell identity loss.
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Affiliation(s)
- Xushen Xiong
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA; Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China
| | - Benjamin T James
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA; The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA
| | - Carles A Boix
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA; The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA
| | - Yongjin P Park
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA; The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA; Department of Pathology and Laboratory Medicine, Department of Statistics, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Kyriaki Galani
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA; The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA
| | - Matheus B Victor
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Na Sun
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA; The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA
| | - Lei Hou
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA; The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA
| | - Li-Lun Ho
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA; The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA
| | - Julio Mantero
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA; The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA
| | - Aine Ni Scannail
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Vishnu Dileep
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Weixiu Dong
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Hansruedi Mathys
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Li-Huei Tsai
- The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA; Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA; The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA.
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159
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Long E, Yin J, Shin JH, Li Y, Kane A, Patel H, Luong T, Xia J, Han Y, Byun J, Zhang T, Zhao W, Landi MT, Rothman N, Lan Q, Chang YS, Yu F, Amos C, Shi J, Lee JG, Kim EY, Choi J. Context-aware single-cell multiome approach identified cell-type specific lung cancer susceptibility genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.25.559336. [PMID: 37808664 PMCID: PMC10557605 DOI: 10.1101/2023.09.25.559336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Accessible chromatin peak detection identified cell-type-specific candidate cis-regulatory elements (cCREs) from each lung cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor abundance and footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare proliferating epithelial cell types, such as AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs, including those in TERT. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including those not detected in tissue- or cell-line-based approaches. cCRE-gene linkage uncovered that adjacent genes expressed in different cell types are correlated with distinct subsets of coinherited CCVs, including JAML and MPZL3 at the 11q23.3 locus. Our data revealed the cell types and contexts where the lung cancer susceptibility genes are functional.
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Affiliation(s)
- Erping Long
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Current affiliation: Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinhu Yin
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ju Hye Shin
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yuyan Li
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Alexander Kane
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Harsh Patel
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Thong Luong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jun Xia
- Department of Biomedical Sciences, Creighton University, Omaha, NE, USA
| | - Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jinyoung Byun
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Wei Zhao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yoon Soo Chang
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Fulong Yu
- Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, China
| | - Christopher Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jin Gu Lee
- Department of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Eun Young Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jiyeon Choi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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160
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Xu D, Forbes AN, Cohen S, Palladino A, Karadimitriou T, Khurana E. Recapitulation of patient-specific 3D chromatin conformation using machine learning. CELL REPORTS METHODS 2023; 3:100578. [PMID: 37673071 PMCID: PMC10545938 DOI: 10.1016/j.crmeth.2023.100578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 04/05/2023] [Accepted: 08/10/2023] [Indexed: 09/08/2023]
Abstract
Regulatory networks containing enhancer-gene edges define cellular states. Multiple efforts have revealed these networks for reference tissues and cell lines by integrating multi-omics data. However, the methods developed cannot be applied for large patient cohorts due to the infeasibility of chromatin immunoprecipitation sequencing (ChIP-seq) for limited biopsy material. We trained machine-learning models using chromatin interaction analysis with paired-end tag sequencing (ChIA-PET) and high-throughput chromosome conformation capture combined with chromatin immunoprecipitation (HiChIP) data that can predict connections using only assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA-seq data as input, which can be generated from biopsies. Our method overcomes limitations of correlation-based approaches that cannot distinguish between distinct target genes of given enhancers or between active vs. poised states in different samples, a hallmark of network rewiring in cancer. Application of our model on 371 samples across 22 cancer types revealed 1,780 enhancer-gene connections for 602 cancer genes. Using CRISPR interference (CRISPRi), we validated enhancers predicted to regulate ESR1 in estrogen receptor (ER)+ breast cancer and A1CF in liver hepatocellular carcinoma.
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Affiliation(s)
- Duo Xu
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA; Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, USA; Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Andre Neil Forbes
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA; Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Sandra Cohen
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Ann Palladino
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA
| | | | - Ekta Khurana
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA; Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, USA; Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA.
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161
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Ying P, Chen C, Lu Z, Chen S, Zhang M, Cai Y, Zhang F, Huang J, Fan L, Ning C, Li Y, Wang W, Geng H, Liu Y, Tian W, Yang Z, Liu J, Huang C, Yang X, Xu B, Li H, Zhu X, Li N, Li B, Wei Y, Zhu Y, Tian J, Miao X. Genome-wide enhancer-gene regulatory maps link causal variants to target genes underlying human cancer risk. Nat Commun 2023; 14:5958. [PMID: 37749132 PMCID: PMC10520073 DOI: 10.1038/s41467-023-41690-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 09/14/2023] [Indexed: 09/27/2023] Open
Abstract
Genome-wide association studies have identified numerous variants associated with human complex traits, most of which reside in the non-coding regions, but biological mechanisms remain unclear. However, assigning function to the non-coding elements is still challenging. Here we apply Activity-by-Contact (ABC) model to evaluate enhancer-gene regulation effect by integrating multi-omics data and identified 544,849 connections across 20 cancer types. ABC model outperforms previous approaches in linking regulatory variants to target genes. Furthermore, we identify over 30,000 enhancer-gene connections in colorectal cancer (CRC) tissues. By integrating large-scale population cohorts (23,813 cases and 29,973 controls) and multipronged functional assays, we demonstrate an ABC regulatory variant rs4810856 associated with CRC risk (Odds Ratio = 1.11, 95%CI = 1.05-1.16, P = 4.02 × 10-5) by acting as an allele-specific enhancer to distally facilitate PREX1, CSE1L and STAU1 expression, which synergistically activate p-AKT signaling. Our study provides comprehensive regulation maps and illuminates a single variant regulating multiple genes, providing insights into cancer etiology.
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Grants
- Distinguished Young Scholars of China (NSFC-81925032), Key Program of National Natural Science Foundation of China (NSFC-82130098), the Fundamental Research Funds for the Central Universities (2042022rc0026, 2042023kf1005),Knowledge Innovation Program of Wuhan (2023020201010060).
- Youth Program of National Natural Science Foundation of China (NSFC-82003547), Program of Health Commission of Hubei Province (WJ2023M045) and Fundamental Research Funds for the Central Universities (WHU: 2042022kf1031).
- The National Science Fund for Excellent Young Scholars (NSFC-82322058), Program of National Natural Science Foundation of China (NSFC-82103929, NSFC-82273713), Young Elite Scientists Sponsorship Program by cst(2022QNRC001), National Science Fund for Distinguished Young Scholars of Hubei Province of China (2023AFA046), Fundamental Research Funds for the Central Universities (WHU:2042022kf1205) and Knowledge Innovation Program of Wuhan (whkxjsj011, 2023020201010073).
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Affiliation(s)
- Pingting Ying
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Can Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Shuoni Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Jinyu Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Linyun Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Wenzhuo Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Hui Geng
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yizhuo Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Wen Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Zhiyong Yang
- Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Jiuyang Liu
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Chaoqun Huang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Xiaojun Yang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Bin Xu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, 430060, China
| | - Heng Li
- Department of Urology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Xu Zhu
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China.
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162
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Cerda-Smith CG, Hutchinson HM, Liu A, Goel VY, Sept C, Kim H, Casaní-Galdón S, Burkman KG, Bassil CF, Hansen AS, Aryee MJ, Johnstone SE, Eyler CE, Wood KC. Integrative PTEN Enhancer Discovery Reveals a New Model of Enhancer Organization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.20.558459. [PMID: 37786671 PMCID: PMC10541578 DOI: 10.1101/2023.09.20.558459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
Enhancers possess both structural elements mediating promoter looping and functional elements mediating gene expression. Traditional models of enhancer-mediated gene regulation imply genomic overlap or immediate adjacency of these elements. We test this model by combining densely-tiled CRISPRa screening with nucleosome-resolution Region Capture Micro-C topology analysis. Using this integrated approach, we comprehensively define the cis-regulatory landscape for the tumor suppressor PTEN, identifying and validating 10 distinct enhancers and defining their 3D spatial organization. Unexpectedly, we identify several long-range functional enhancers whose promoter proximity is facilitated by chromatin loop anchors several kilobases away, and demonstrate that accounting for this spatial separation improves the computational prediction of validated enhancers. Thus, we propose a new model of enhancer organization incorporating spatial separation of essential functional and structural components.
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Affiliation(s)
- Christian G. Cerda-Smith
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine; Durham, NC 27710, USA
| | - Haley M. Hutchinson
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine; Durham, NC 27710, USA
| | - Annie Liu
- Department of Surgery, Duke University School of Medicine; Durham, NC 27710, USA
| | - Viraat Y. Goel
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, 02139, USA
- Broad Institute; Cambridge, MA 02139, USA
- Koch Institute for Integrative Cancer Research; Cambridge, MA, 02139, USA
| | - Corriene Sept
- Broad Institute; Cambridge, MA 02139, USA
- Department of Biostatistics, Harvard School of Public Health; Boston, MA 02215, USA
| | - Holly Kim
- Department of Radiation Oncology, Duke University School of Medicine; Durham, NC 27710, USA
| | - Salvador Casaní-Galdón
- Broad Institute; Cambridge, MA 02139, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute; Boston, MA 02215, USA
- Departments of Cell Biology and Pathology, Harvard Medical School; Boston, MA 02114, USA
| | - Katherine G. Burkman
- Department of Radiation Oncology, Duke University School of Medicine; Durham, NC 27710, USA
| | - Christopher F. Bassil
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine; Durham, NC 27710, USA
| | - Anders S. Hansen
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, 02139, USA
- Broad Institute; Cambridge, MA 02139, USA
- Koch Institute for Integrative Cancer Research; Cambridge, MA, 02139, USA
| | - Martin J. Aryee
- Broad Institute; Cambridge, MA 02139, USA
- Department of Pathology, Harvard Medical School; Boston, MA 02114, USA
- Department of Data Science, Dana-Farber Cancer Institute; Boston, MA 02215, USA
| | - Sarah E. Johnstone
- Broad Institute; Cambridge, MA 02139, USA
- Department of Pathology, Dana-Farber Cancer Institute; Boston, MA 02215, USA
| | - Christine E. Eyler
- Department of Radiation Oncology, Duke University School of Medicine; Durham, NC 27710, USA
- Duke Cancer Institute, Duke University School of Medicine; Durham, NC 27710, USA
| | - Kris C. Wood
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine; Durham, NC 27710, USA
- Duke Cancer Institute, Duke University School of Medicine; Durham, NC 27710, USA
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163
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Li X, Lappalainen T, Bussemaker HJ. Identifying genetic regulatory variants that affect transcription factor activity. CELL GENOMICS 2023; 3:100382. [PMID: 37719147 PMCID: PMC10504674 DOI: 10.1016/j.xgen.2023.100382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 05/19/2023] [Accepted: 07/21/2023] [Indexed: 09/19/2023]
Abstract
Genetic variants affecting gene expression levels in humans have been mapped in the Genotype-Tissue Expression (GTEx) project. Trans-acting variants impacting many genes simultaneously through a shared transcription factor (TF) are of particular interest. Here, we developed a generalized linear model (GLM) to estimate protein-level TF activity levels in an individual-specific manner from GTEx RNA sequencing (RNA-seq) profiles. It uses observed differential gene expression after TF perturbation as a predictor and, by analyzing differential expression within pairs of neighboring genes, controls for the confounding effect of variation in chromatin state along the genome. We inferred genotype-specific activities for 55 TFs across 49 tissues. Subsequently performing genome-wide association analysis on this virtual trait revealed TF activity quantitative trait loci (aQTLs) that, as a set, are enriched for functional features. Altogether, the set of tools we introduce here highlights the potential of genetic association studies for cellular endophenotypes based on a network-based multi-omics approach. The transparent peer review record is available.
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Affiliation(s)
- Xiaoting Li
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY 10013, USA
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
| | - Harmen J. Bussemaker
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
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164
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Song C, Zhang Y, Huang H, Wang Y, Zhao X, Zhang G, Yin M, Feng C, Wang Q, Qian F, Shang D, Zhang J, Liu J, Li C, Tang H. Cis-Cardio: A comprehensive analysis platform for cardiovascular-relavant cis-regulation in human and mouse. MOLECULAR THERAPY. NUCLEIC ACIDS 2023; 33:655-667. [PMID: 37637211 PMCID: PMC10458290 DOI: 10.1016/j.omtn.2023.07.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 07/25/2023] [Indexed: 08/29/2023]
Abstract
Cis-regulatory elements are important molecular switches in controlling gene expression and are regarded as determinant hubs in the transcriptional regulatory network. Collection and processing of large-scale cis-regulatory data are urgent to decipher the potential mechanisms of cardiovascular diseases from a cis-regulatory element aspect. Here, we developed a novel web server, Cis-Cardio, which aims to document a large number of available cardiovascular-related cis-regulatory data and to provide analysis for unveiling the comprehensive mechanisms at a cis-regulation level. The current version of Cis-Cardio catalogs a total of 45,382,361 genomic regions from 1,013 human and mouse epigenetic datasets, including ATAC-seq, DNase-seq, Histone ChIP-seq, TF/TcoF ChIP-seq, RNA polymerase ChIP-seq, and Cohesin ChIP-seq. Importantly, Cis-Cardio provides six analysis tools, including region overlap analysis, element upstream/downstream analysis, transcription regulator enrichment analysis, variant interpretation, and protein-protein interaction-based co-regulatory analysis. Additionally, Cis-Cardio provides detailed and abundant (epi-) genetic annotations in cis-regulatory regions, such as super-enhancers, enhancers, transcription factor binding sites (TFBSs), methylation sites, common SNPs, risk SNPs, expression quantitative trait loci (eQTLs), motifs, DNase I hypersensitive sites (DHSs), and 3D chromatin interactions. In summary, Cis-Cardio is a valuable resource for elucidating and analyzing regulatory cues of cardiovascular-specific cis-regulatory elements. The platform is freely available at http://www.licpathway.net/Cis-Cardio/index.html.
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Affiliation(s)
- Chao Song
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
| | - Yuexin Zhang
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
| | - Hong Huang
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
- Clinical Research Center for Myocardial Injury in Hunan Province, Hengyang, Hunan 421001, China
| | - Yuezhu Wang
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Xilong Zhao
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Guorui Zhang
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
| | - Mingxue Yin
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
| | - Chenchen Feng
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Qiuyu Wang
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Fengcui Qian
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
| | - Desi Shang
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Jian Zhang
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Jiaqi Liu
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
| | - Chunquan Li
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan 410008, China
- Key Laboratory of Rare Pediatric Diseases, Ministry of Education, University of South China, Hengyang, Hunan 421001, China
| | - Huifang Tang
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
- Clinical Research Center for Myocardial Injury in Hunan Province, Hengyang, Hunan 421001, China
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165
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Yang J, Zhu X, Wang R, Li M, Tang Q. Revisiting Assessment of Computational Methods for Hi-C Data Analysis. Int J Mol Sci 2023; 24:13814. [PMID: 37762117 PMCID: PMC10531246 DOI: 10.3390/ijms241813814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/30/2023] [Accepted: 09/03/2023] [Indexed: 09/29/2023] Open
Abstract
The performances of algorithms for Hi-C data preprocessing, the identification of topologically associating domains, and the detection of chromatin interactions and promoter-enhancer interactions have been mostly evaluated using semi-quantitative or synthetic data approaches, without utilizing the most recent methods, since 2017. In this study, we comprehensively evaluated 24 popular state-of-the-art methods for the complete end-to-end pipeline of Hi-C data analysis, using manually curated or experimentally validated benchmark datasets, including a CRISPR dataset for promoter-enhancer interaction validation. Our results indicate that, although no single method exhibited superior performance in all situations, HiC-Pro, DomainCaller, and Fit-Hi-C2 showed relatively balanced performances of most evaluation metrics for preprocessing, topologically associating domain identification, and chromatin interaction/promoter-enhancer interaction detection, respectively. The comprehensive comparison presented in this manuscript provides a reference for researchers to choose Hi-C analysis tools that best suit their needs.
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Affiliation(s)
- Jing Yang
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (J.Y.); (X.Z.); (R.W.)
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
| | - Xingxing Zhu
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (J.Y.); (X.Z.); (R.W.)
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
| | - Rui Wang
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (J.Y.); (X.Z.); (R.W.)
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
| | - Mingzhou Li
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (J.Y.); (X.Z.); (R.W.)
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
| | - Qianzi Tang
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (J.Y.); (X.Z.); (R.W.)
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
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166
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Kerimov N, Tambets R, Hayhurst JD, Rahu I, Kolberg P, Raudvere U, Kuzmin I, Chowdhary A, Vija A, Teras HJ, Kanai M, Ulirsch J, Ryten M, Hardy J, Guelfi S, Trabzuni D, Kim-Hellmuth S, Rayner W, Finucane H, Peterson H, Mosaku A, Parkinson H, Alasoo K. eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs. PLoS Genet 2023; 19:e1010932. [PMID: 37721944 PMCID: PMC10538656 DOI: 10.1371/journal.pgen.1010932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 09/28/2023] [Accepted: 08/22/2023] [Indexed: 09/20/2023] Open
Abstract
The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.
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Affiliation(s)
- Nurlan Kerimov
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Ralf Tambets
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - James D. Hayhurst
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Ida Rahu
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Peep Kolberg
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Uku Raudvere
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Ivan Kuzmin
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Anshika Chowdhary
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Andreas Vija
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Hans J. Teras
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Jacob Ulirsch
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Mina Ryten
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - John Hardy
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Sebastian Guelfi
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Daniah Trabzuni
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Sarah Kim-Hellmuth
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
- Department of Pediatrics, Dr. von Hauner Children’s Hospital, University Hospital LMU Munich, Munich, Germany
| | - William Rayner
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Hilary Finucane
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Hedi Peterson
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Abayomi Mosaku
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Helen Parkinson
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Kaur Alasoo
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
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167
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Karttunen K, Patel D, Xia J, Fei L, Palin K, Aaltonen L, Sahu B. Transposable elements as tissue-specific enhancers in cancers of endodermal lineage. Nat Commun 2023; 14:5313. [PMID: 37658059 PMCID: PMC10474299 DOI: 10.1038/s41467-023-41081-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 08/23/2023] [Indexed: 09/03/2023] Open
Abstract
Transposable elements (TE) are repetitive genomic elements that harbor binding sites for human transcription factors (TF). A regulatory role for TEs has been suggested in embryonal development and diseases such as cancer but systematic investigation of their functions has been limited by their widespread silencing in the genome. Here, we utilize unbiased massively parallel reporter assay data using a whole human genome library to identify TEs with functional enhancer activity in two human cancer types of endodermal lineage, colorectal and liver cancers. We show that the identified TE enhancers are characterized by genomic features associated with active enhancers, such as epigenetic marks and TF binding. Importantly, we identify distinct TE subfamilies that function as tissue-specific enhancers, namely MER11- and LTR12-elements in colon and liver cancers, respectively. These elements are bound by distinct TFs in each cell type, and they have predicted associations to differentially expressed genes. In conclusion, these data demonstrate how different cancer types can utilize distinct TEs as tissue-specific enhancers, paving the way for comprehensive understanding of the role of TEs as bona fide enhancers in the cancer genomes.
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Affiliation(s)
- Konsta Karttunen
- Applied Tumor Genomics Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Divyesh Patel
- Applied Tumor Genomics Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland
| | - Jihan Xia
- Applied Tumor Genomics Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland
| | - Liangru Fei
- Applied Tumor Genomics Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Kimmo Palin
- Applied Tumor Genomics Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland
| | - Lauri Aaltonen
- Applied Tumor Genomics Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland
| | - Biswajyoti Sahu
- Applied Tumor Genomics Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland.
- Medicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- Centre for Molecular Medicine Norway, University of Oslo, Oslo, Norway.
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168
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Bravo González-Blas C, De Winter S, Hulselmans G, Hecker N, Matetovici I, Christiaens V, Poovathingal S, Wouters J, Aibar S, Aerts S. SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks. Nat Methods 2023; 20:1355-1367. [PMID: 37443338 PMCID: PMC10482700 DOI: 10.1038/s41592-023-01938-4] [Citation(s) in RCA: 85] [Impact Index Per Article: 85.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 06/06/2023] [Indexed: 07/15/2023]
Abstract
Joint profiling of chromatin accessibility and gene expression in individual cells provides an opportunity to decipher enhancer-driven gene regulatory networks (GRNs). Here we present a method for the inference of enhancer-driven GRNs, called SCENIC+. SCENIC+ predicts genomic enhancers along with candidate upstream transcription factors (TFs) and links these enhancers to candidate target genes. To improve both recall and precision of TF identification, we curated and clustered a motif collection with more than 30,000 motifs. We benchmarked SCENIC+ on diverse datasets from different species, including human peripheral blood mononuclear cells, ENCODE cell lines, melanoma cell states and Drosophila retinal development. Next, we exploit SCENIC+ predictions to study conserved TFs, enhancers and GRNs between human and mouse cell types in the cerebral cortex. Finally, we use SCENIC+ to study the dynamics of gene regulation along differentiation trajectories and the effect of TF perturbations on cell state. SCENIC+ is available at scenicplus.readthedocs.io .
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Affiliation(s)
- Carmen Bravo González-Blas
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Seppe De Winter
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Gert Hulselmans
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Nikolai Hecker
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Irina Matetovici
- VIB Center for Brain & Disease Research, Leuven, Belgium
- VIB Tech Watch, VIB Headquarters, Ghent, Belgium
| | - Valerie Christiaens
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | | | - Jasper Wouters
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Sara Aibar
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Stein Aerts
- VIB Center for Brain & Disease Research, Leuven, Belgium.
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
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169
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Zhu W, Li H, Dong P, Ni X, Fan M, Yang Y, Xu S, Xu Y, Qian Y, Chen Z, Lü P. Low temperature-induced regulatory network rewiring via WRKY regulators during banana peel browning. PLANT PHYSIOLOGY 2023; 193:855-873. [PMID: 37279567 PMCID: PMC10469544 DOI: 10.1093/plphys/kiad322] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/10/2023] [Accepted: 05/11/2023] [Indexed: 06/08/2023]
Abstract
Banana (Musa spp.) fruits, as typical tropical fruits, are cold sensitive, and lower temperatures can disrupt cellular compartmentalization and lead to severe browning. How tropical fruits respond to low temperature compared to the cold response mechanisms of model plants remains unknown. Here, we systematically characterized the changes in chromatin accessibility, histone modifications, distal cis-regulatory elements, transcription factor binding, and gene expression levels in banana peels in response to low temperature. Dynamic patterns of cold-induced transcripts were generally accompanied by concordant chromatin accessibility and histone modification changes. These upregulated genes were enriched for WRKY binding sites in their promoters and/or active enhancers. Compared to banana peel at room temperature, large amounts of banana WRKYs were specifically induced by cold and mediated enhancer-promoter interactions regulating critical browning pathways, including phospholipid degradation, oxidation, and cold tolerance. This hypothesis was supported by DNA affinity purification sequencing, luciferase reporter assays, and transient expression assay. Together, our findings highlight widespread transcriptional reprogramming via WRKYs during banana peel browning at low temperature and provide an extensive resource for studying gene regulation in tropical plants in response to cold stress, as well as potential targets for improving cold tolerance and shelf life of tropical fruits.
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Affiliation(s)
- Wenjun Zhu
- Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Hua Li
- Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Pengfei Dong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Xueting Ni
- Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Minlei Fan
- Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Yingjie Yang
- Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Shiyao Xu
- Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Yanbing Xu
- Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Yangwen Qian
- WIMI Biotechnology Co., Ltd., Changzhou 213000, China
| | - Zhuo Chen
- Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Peitao Lü
- Fujian Agriculture and Forestry University, Fuzhou 350002, China
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170
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Mohana G, Dorier J, Li X, Mouginot M, Smith RC, Malek H, Leleu M, Rodriguez D, Khadka J, Rosa P, Cousin P, Iseli C, Restrepo S, Guex N, McCabe BD, Jankowski A, Levine MS, Gambetta MC. Chromosome-level organization of the regulatory genome in the Drosophila nervous system. Cell 2023; 186:3826-3844.e26. [PMID: 37536338 PMCID: PMC10529364 DOI: 10.1016/j.cell.2023.07.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 03/31/2023] [Accepted: 07/06/2023] [Indexed: 08/05/2023]
Abstract
Previous studies have identified topologically associating domains (TADs) as basic units of genome organization. We present evidence of a previously unreported level of genome folding, where distant TAD pairs, megabases apart, interact to form meta-domains. Within meta-domains, gene promoters and structural intergenic elements present in distant TADs are specifically paired. The associated genes encode neuronal determinants, including those engaged in axonal guidance and adhesion. These long-range associations occur in a large fraction of neurons but support transcription in only a subset of neurons. Meta-domains are formed by diverse transcription factors that are able to pair over long and flexible distances. We present evidence that two such factors, GAF and CTCF, play direct roles in this process. The relative simplicity of higher-order meta-domain interactions in Drosophila, compared with those previously described in mammals, allowed the demonstration that genomes can fold into highly specialized cell-type-specific scaffolds that enable megabase-scale regulatory associations.
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Affiliation(s)
- Giriram Mohana
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Julien Dorier
- Bioinformatics Competence Center, University of Lausanne, 1015 Lausanne, Switzerland; Bioinformatics Competence Center, Swiss Federal Institute of Technology Lausanne, 1015 Lausanne, Switzerland
| | - Xiao Li
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Marion Mouginot
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Rebecca C Smith
- Brain Mind Institute, Swiss Federal Institute of Technology Lausanne, 1015 Lausanne, Switzerland
| | - Héléna Malek
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Marion Leleu
- Bioinformatics Competence Center, University of Lausanne, 1015 Lausanne, Switzerland; Bioinformatics Competence Center, Swiss Federal Institute of Technology Lausanne, 1015 Lausanne, Switzerland
| | - Daniel Rodriguez
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Jenisha Khadka
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Patrycja Rosa
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, 02-097 Warsaw, Poland
| | - Pascal Cousin
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Christian Iseli
- Bioinformatics Competence Center, University of Lausanne, 1015 Lausanne, Switzerland; Bioinformatics Competence Center, Swiss Federal Institute of Technology Lausanne, 1015 Lausanne, Switzerland
| | - Simon Restrepo
- Arcoris bio AG, Lüssirainstrasse 52, 6300 Zug, Switzerland
| | - Nicolas Guex
- Bioinformatics Competence Center, University of Lausanne, 1015 Lausanne, Switzerland; Bioinformatics Competence Center, Swiss Federal Institute of Technology Lausanne, 1015 Lausanne, Switzerland
| | - Brian D McCabe
- Brain Mind Institute, Swiss Federal Institute of Technology Lausanne, 1015 Lausanne, Switzerland
| | - Aleksander Jankowski
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, 02-097 Warsaw, Poland.
| | - Michael S Levine
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.
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171
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Selewa A, Luo K, Wasney M, Smith L, Sun X, Tang C, Eckart H, Moskowitz IP, Basu A, He X, Pott S. Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation. Nat Commun 2023; 14:4999. [PMID: 37591828 PMCID: PMC10435551 DOI: 10.1038/s41467-023-40505-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 08/01/2023] [Indexed: 08/19/2023] Open
Abstract
Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 46 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits.
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Affiliation(s)
- Alan Selewa
- Biophysical Sciences Graduate Program, The University of Chicago, Chicago, IL, 60637, USA
| | - Kaixuan Luo
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA
| | - Michael Wasney
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Linsin Smith
- Committee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA
| | - Xiaotong Sun
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA
| | - Chenwei Tang
- The College, The University of Chicago, Chicago, IL, 60637, USA
| | - Heather Eckart
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Ivan P Moskowitz
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA
- Department of Pediatrics, The University of Chicago, Chicago, IL, 60637, USA
| | - Anindita Basu
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA.
| | - Xin He
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA.
| | - Sebastian Pott
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA.
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172
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Berson E, Sreenivas A, Phongpreecha T, Perna A, Grandi FC, Xue L, Ravindra NG, Payrovnaziri N, Mataraso S, Kim Y, Espinosa C, Chang AL, Becker M, Montine KS, Fox EJ, Chang HY, Corces MR, Aghaeepour N, Montine TJ. Whole genome deconvolution unveils Alzheimer's resilient epigenetic signature. Nat Commun 2023; 14:4947. [PMID: 37587197 PMCID: PMC10432546 DOI: 10.1038/s41467-023-40611-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 08/03/2023] [Indexed: 08/18/2023] Open
Abstract
Assay for Transposase Accessible Chromatin by sequencing (ATAC-seq) accurately depicts the chromatin regulatory state and altered mechanisms guiding gene expression in disease. However, bulk sequencing entangles information from different cell types and obscures cellular heterogeneity. To address this, we developed Cellformer, a deep learning method that deconvolutes bulk ATAC-seq into cell type-specific expression across the whole genome. Cellformer enables cost-effective cell type-specific open chromatin profiling in large cohorts. Applied to 191 bulk samples from 3 brain regions, Cellformer identifies cell type-specific gene regulatory mechanisms involved in resilience to Alzheimer's disease, an uncommon group of cognitively healthy individuals that harbor a high pathological load of Alzheimer's disease. Cell type-resolved chromatin profiling unveils cell type-specific pathways and nominates potential epigenetic mediators underlying resilience that may illuminate therapeutic opportunities to limit the cognitive impact of the disease. Cellformer is freely available to facilitate future investigations using high-throughput bulk ATAC-seq data.
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Affiliation(s)
- Eloise Berson
- Department of Pathology, Stanford University, Stanford, CA, USA.
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA.
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
| | - Anjali Sreenivas
- Department of Pathology, Stanford University, Stanford, CA, USA
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
| | - Thanaphong Phongpreecha
- Department of Pathology, Stanford University, Stanford, CA, USA
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Amalia Perna
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Fiorella C Grandi
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Lei Xue
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Neal G Ravindra
- Department of Pathology, Stanford University, Stanford, CA, USA
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Neelufar Payrovnaziri
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Samson Mataraso
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Yeasul Kim
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Camilo Espinosa
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Alan L Chang
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Martin Becker
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford University, Stanford, CA, USA
| | | | - Edward J Fox
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - M Ryan Corces
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford University, Stanford, CA, USA
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173
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Monti R, Ohler U. Toward Identification of Functional Sequences and Variants in Noncoding DNA. Annu Rev Biomed Data Sci 2023; 6:191-210. [PMID: 37262323 DOI: 10.1146/annurev-biodatasci-122120-110102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Understanding the noncoding part of the genome, which encodes gene regulation, is necessary to identify genetic mechanisms of disease and translate findings from genome-wide association studies into actionable results for treatments and personalized care. Here we provide an overview of the computational analysis of noncoding regions, starting from gene-regulatory mechanisms and their representation in data. Deep learning methods, when applied to these data, highlight important regulatory sequence elements and predict the functional effects of genetic variants. These and other algorithms are used to predict damaging sequence variants. Finally, we introduce rare-variant association tests that incorporate functional annotations and predictions in order to increase interpretability and statistical power.
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Affiliation(s)
- Remo Monti
- Max Delbrück Center for Molecular Medicine (MDC), Helmholtz Association of German Research Centers, Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany;
- Digital Health-Machine Learning, Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
| | - Uwe Ohler
- Max Delbrück Center for Molecular Medicine (MDC), Helmholtz Association of German Research Centers, Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany;
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174
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Choi J, Kim S, Kim J, Son HY, Yoo SK, Kim CU, Park YJ, Moon S, Cha B, Jeon MC, Park K, Yun JM, Cho B, Kim N, Kim C, Kwon NJ, Park YJ, Matsuda F, Momozawa Y, Kubo M, Kim HJ, Park JH, Seo JS, Kim JI, Im SW. A whole-genome reference panel of 14,393 individuals for East Asian populations accelerates discovery of rare functional variants. SCIENCE ADVANCES 2023; 9:eadg6319. [PMID: 37556544 PMCID: PMC10411914 DOI: 10.1126/sciadv.adg6319] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 07/06/2023] [Indexed: 08/11/2023]
Abstract
Underrepresentation of non-European (EUR) populations hinders growth of global precision medicine. Resources such as imputation reference panels that match the study population are necessary to find low-frequency variants with substantial effects. We created a reference panel consisting of 14,393 whole-genome sequences including more than 11,000 Asian individuals. Genome-wide association studies were conducted using the reference panel and a population-specific genotype array of 72,298 subjects for eight phenotypes. This panel yields improved imputation accuracy of rare and low-frequency variants within East Asian populations compared with the largest reference panel. Thirty-nine previously unidentified associations were found, and more than half of the variants were East Asian specific. We discovered genes with rare protein-altering variants, including LTBP1 for height and GPR75 for body mass index, as well as putative regulatory mechanisms for rare noncoding variants with cell type-specific effects. We suggest that this dataset will add to the potential value of Asian precision medicine.
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Affiliation(s)
- Jaeyong Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | | | - Juhyun Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ho-Young Son
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Seong-Keun Yoo
- The Marc and Jennifer Lipschultz Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Young Jun Park
- Department of Translational Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sungji Moon
- Interdisciplinary Program in Cancer Biology, Seoul National University College of Medicine, Seoul, Republic of Korea
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - Bukyoung Cha
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Min Chul Jeon
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kyunghyuk Park
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Jae Moon Yun
- Department of Family Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Belong Cho
- Department of Family Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Family Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | | | | | | | - Young Joo Park
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | | | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Hyun-Jin Kim
- National Cancer Control Institute, National Cancer Center, Goyang, Republic of Korea
| | - Jin-Ho Park
- Department of Family Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Family Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jeong-Sun Seo
- Macrogen Inc., Seoul, Republic of Korea
- Asian Genome Center, Seoul National University Bundang Hospital, Gyeonggi, Republic of Korea
| | - Jong-Il Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
- Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sun-Wha Im
- Department of Biochemistry and Molecular Biology, Kangwon National University School of Medicine, Gangwon, Republic of Korea
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175
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Yankee TN, Oh S, Winchester EW, Wilderman A, Robinson K, Gordon T, Rosenfeld JA, VanOudenhove J, Scott DA, Leslie EJ, Cotney J. Integrative analysis of transcriptome dynamics during human craniofacial development identifies candidate disease genes. Nat Commun 2023; 14:4623. [PMID: 37532691 PMCID: PMC10397224 DOI: 10.1038/s41467-023-40363-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 07/25/2023] [Indexed: 08/04/2023] Open
Abstract
Craniofacial disorders arise in early pregnancy and are one of the most common congenital defects. To fully understand how craniofacial disorders arise, it is essential to characterize gene expression during the patterning of the craniofacial region. To address this, we performed bulk and single-cell RNA-seq on human craniofacial tissue from 4-8 weeks post conception. Comparisons to dozens of other human tissues revealed 239 genes most strongly expressed during craniofacial development. Craniofacial-biased developmental enhancers were enriched +/- 400 kb surrounding these craniofacial-biased genes. Gene co-expression analysis revealed that regulatory hubs are enriched for known disease causing genes and are resistant to mutation in the normal healthy population. Combining transcriptomic and epigenomic data we identified 539 genes likely to contribute to craniofacial disorders. While most have not been previously implicated in craniofacial disorders, we demonstrate this set of genes has increased levels of de novo mutations in orofacial clefting patients warranting further study.
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Affiliation(s)
- Tara N Yankee
- Graduate Program in Genetics and Developmental Biology, UConn Health, Farmington, CT, 06030, USA
| | - Sungryong Oh
- University of Connecticut School of Medicine, Department of Genetics and Genome Sciences, Farmington, CT, 06030, USA
| | | | - Andrea Wilderman
- Graduate Program in Genetics and Developmental Biology, UConn Health, Farmington, CT, 06030, USA
| | - Kelsey Robinson
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Tia Gordon
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Jill A Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Baylor Genetics Laboratory, Houston, TX, 77021, USA
| | - Jennifer VanOudenhove
- University of Connecticut School of Medicine, Department of Genetics and Genome Sciences, Farmington, CT, 06030, USA
| | - Daryl A Scott
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Elizabeth J Leslie
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Justin Cotney
- University of Connecticut School of Medicine, Department of Genetics and Genome Sciences, Farmington, CT, 06030, USA.
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, 06269, USA.
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176
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Bond ML, Davis ES, Quiroga IY, Dey A, Kiran M, Love MI, Won H, Phanstiel DH. Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features. Genome Res 2023; 33:1258-1268. [PMID: 37699658 PMCID: PMC10547260 DOI: 10.1101/gr.277397.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 07/07/2023] [Indexed: 09/14/2023]
Abstract
Three-dimensional (3D) chromatin structure has been shown to play a role in regulating gene transcription during biological transitions. Although our understanding of loop formation and maintenance is rapidly improving, much less is known about the mechanisms driving changes in looping and the impact of differential looping on gene transcription. One limitation has been a lack of well-powered differential looping data sets. To address this, we conducted a deeply sequenced Hi-C time course of megakaryocyte development comprising four biological replicates and 6 billion reads per time point. Statistical analysis revealed 1503 differential loops. Gained loop anchors were enriched for AP-1 occupancy and were characterized by large increases in histone H3K27ac (over 11-fold) but relatively small increases in CTCF and RAD21 binding (1.26- and 1.23-fold, respectively). Linear modeling revealed that changes in histone H3K27ac, chromatin accessibility, and JUN binding were better correlated with changes in looping than RAD21 and almost as well correlated as CTCF. Changes to epigenetic features between-rather than at-boundaries were highly predictive of changes in looping. Together these data suggest that although CTCF and RAD21 may be the core machinery dictating where loops form, other features (both at the anchors and within the loop boundaries) may play a larger role than previously anticipated in determining the relative loop strength across cell types and conditions.
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Affiliation(s)
- Marielle L Bond
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Eric S Davis
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Ivana Y Quiroga
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Anubha Dey
- Department of Systems and Computational Biology, University of Hyderabad, Hyderabad 500046, Telangana, India
| | - Manjari Kiran
- Department of Systems and Computational Biology, University of Hyderabad, Hyderabad 500046, Telangana, India
| | - Michael I Love
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514, USA
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514, USA;
- Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Douglas H Phanstiel
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA;
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
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177
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Luo R, Yan J, Oh JW, Xi W, Shigaki D, Wong W, Cho HS, Murphy D, Cutler R, Rosen BP, Pulecio J, Yang D, Glenn RA, Chen T, Li QV, Vierbuchen T, Sidoli S, Apostolou E, Huangfu D, Beer MA. Dynamic network-guided CRISPRi screen identifies CTCF-loop-constrained nonlinear enhancer gene regulatory activity during cell state transitions. Nat Genet 2023; 55:1336-1346. [PMID: 37488417 PMCID: PMC11012226 DOI: 10.1038/s41588-023-01450-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 06/20/2023] [Indexed: 07/26/2023]
Abstract
Comprehensive enhancer discovery is challenging because most enhancers, especially those contributing to complex diseases, have weak effects on gene expression. Our gene regulatory network modeling identified that nonlinear enhancer gene regulation during cell state transitions can be leveraged to improve the sensitivity of enhancer discovery. Using human embryonic stem cell definitive endoderm differentiation as a dynamic transition system, we conducted a mid-transition CRISPRi-based enhancer screen. We discovered a comprehensive set of enhancers for each of the core endoderm-specifying transcription factors. Many enhancers had strong effects mid-transition but weak effects post-transition, consistent with the nonlinear temporal responses to enhancer perturbation predicted by the modeling. Integrating three-dimensional genomic information, we were able to develop a CTCF-loop-constrained Interaction Activity model that can better predict functional enhancers compared to models that rely on Hi-C-based enhancer-promoter contact frequency. Our study provides generalizable strategies for sensitive and systematic enhancer discovery in both normal and pathological cell state transitions.
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Affiliation(s)
- Renhe Luo
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Jielin Yan
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Jin Woo Oh
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Wang Xi
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Dustin Shigaki
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Wilfred Wong
- Computational & Systems Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York City, NY, USA
| | - Hyein S Cho
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
| | - Dylan Murphy
- Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York City, NY, USA
- Department of Medicine, Weill Cornell Medicine, New York City, NY, USA
| | - Ronald Cutler
- Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Bess P Rosen
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York City, NY, USA
| | - Julian Pulecio
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
| | - Dapeng Yang
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
| | - Rachel A Glenn
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York City, NY, USA
| | - Tingxu Chen
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Qing V Li
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Thomas Vierbuchen
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
| | - Simone Sidoli
- Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Effie Apostolou
- Department of Medicine, Weill Cornell Medicine, New York City, NY, USA
| | - Danwei Huangfu
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA.
| | - Michael A Beer
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA.
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178
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Barshad G, Lewis JJ, Chivu AG, Abuhashem A, Krietenstein N, Rice EJ, Ma Y, Wang Z, Rando OJ, Hadjantonakis AK, Danko CG. RNA polymerase II dynamics shape enhancer-promoter interactions. Nat Genet 2023; 55:1370-1380. [PMID: 37430091 DOI: 10.1038/s41588-023-01442-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 06/09/2023] [Indexed: 07/12/2023]
Abstract
How enhancers control target gene expression over long genomic distances remains an important unsolved problem. Here we investigated enhancer-promoter communication by integrating data from nucleosome-resolution genomic contact maps, nascent transcription and perturbations affecting either RNA polymerase II (Pol II) dynamics or the activity of thousands of candidate enhancers. Integration of new Micro-C experiments with published CRISPRi data demonstrated that enhancers spend more time in close proximity to their target promoters in functional enhancer-promoter pairs compared to nonfunctional pairs, which can be attributed in part to factors unrelated to genomic position. Manipulation of the transcription cycle demonstrated a key role for Pol II in enhancer-promoter interactions. Notably, promoter-proximal paused Pol II itself partially stabilized interactions. We propose an updated model in which elements of transcriptional dynamics shape the duration or frequency of interactions to facilitate enhancer-promoter communication.
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Affiliation(s)
- Gilad Barshad
- Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA
| | - James J Lewis
- Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC, USA
| | - Alexandra G Chivu
- Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA
| | - Abderhman Abuhashem
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
- Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program, New York City, NY, USA
- Biochemistry Cell and Molecular Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York City, NY, USA
| | - Nils Krietenstein
- The Novo Nordisk Center for Protein Research (CPR), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Edward J Rice
- Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA
| | - Yitian Ma
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
| | - Zhong Wang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
| | - Oliver J Rando
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Anna-Katerina Hadjantonakis
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
- Biochemistry Cell and Molecular Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York City, NY, USA
| | - Charles G Danko
- Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.
- Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.
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179
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Weeks EM, Ulirsch JC, Cheng NY, Trippe BL, Fine RS, Miao J, Patwardhan TA, Kanai M, Nasser J, Fulco CP, Tashman KC, Aguet F, Li T, Ordovas-Montanes J, Smillie CS, Biton M, Shalek AK, Ananthakrishnan AN, Xavier RJ, Regev A, Gupta RM, Lage K, Ardlie KG, Hirschhorn JN, Lander ES, Engreitz JM, Finucane HK. Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases. Nat Genet 2023; 55:1267-1276. [PMID: 37443254 PMCID: PMC10836580 DOI: 10.1038/s41588-023-01443-6] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 06/09/2023] [Indexed: 07/15/2023]
Abstract
Genome-wide association studies (GWASs) are a valuable tool for understanding the biology of complex human traits and diseases, but associated variants rarely point directly to causal genes. In the present study, we introduce a new method, polygenic priority score (PoPS), that learns trait-relevant gene features, such as cell-type-specific expression, to prioritize genes at GWAS loci. Using a large evaluation set of genes with fine-mapped coding variants, we show that PoPS and the closest gene individually outperform other gene prioritization methods, but observe the best overall performance by combining PoPS with orthogonal methods. Using this combined approach, we prioritize 10,642 unique gene-trait pairs across 113 complex traits and diseases with high precision, finding not only well-established gene-trait relationships but nominating new genes at unresolved loci, such as LGR4 for estimated glomerular filtration rate and CCR7 for deep vein thrombosis. Overall, we demonstrate that PoPS provides a powerful addition to the gene prioritization toolbox.
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Affiliation(s)
- Elle M Weeks
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Jacob C Ulirsch
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA, USA
| | | | - Brian L Trippe
- Program in Computational & Systems Biology, MIT, Cambridge, MA, USA
- Computer Science & Artificial Intelligence Lab, MIT, Cambridge, MA, USA
| | - Rebecca S Fine
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Vertex Pharmaceuticals Incorporated, Boston, MA, USA
| | - Jenkai Miao
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
| | - Tejal A Patwardhan
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Masahiro Kanai
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, MGH, Boston, MA, USA
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Joseph Nasser
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Charles P Fulco
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Bristol Myers Squibb, Cambridge, MA, USA
| | | | | | - Taibo Li
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- MD-PhD Program, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jose Ordovas-Montanes
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Gastroenterology, Hepatology, and Nutrition, Boston Children's Hospital, Boston, MA, USA
- Program in Immunology, Harvard Medical School, Boston, MA, USA
- Harvard Stem Cell Institute, Cambridge, MA, USA
| | - Christopher S Smillie
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Computational & Systems Biology, MIT, Cambridge, MA, USA
| | - Moshe Biton
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Molecular Biology, MGH, Boston, MA, USA
- Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel
| | - Alex K Shalek
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Medical Engineering and Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Ragon Institute of MGH, MMIT, Cambridge, MA, USA
| | - Ashwin N Ananthakrishnan
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease, MGH, Boston, MA, USA
| | - Ramnik J Xavier
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Molecular Biology, MGH, Boston, MA, USA
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease, MGH, Boston, MA, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Aviv Regev
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Howard Hughes Medical Institute, MIT, Cambridge, MA, USA
- Genentech, San Francisco, CA, USA
| | - Rajat M Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Cardiovascular Medicine and Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Kasper Lage
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Surgery, MGH, Boston, MA, USA
| | - Kristin G Ardlie
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Joel N Hirschhorn
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Eric S Lander
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biology, MIT, Cambridge, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Jesse M Engreitz
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- BASE Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford University School of Medicine, Stanford, CA, USA
| | - Hilary K Finucane
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Analytic and Translational Genetics Unit, MGH, Boston, MA, USA.
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180
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Ober-Reynolds B, Wang C, Ko JM, Rios EJ, Aasi SZ, Davis MM, Oro AE, Greenleaf WJ. Integrated single-cell chromatin and transcriptomic analyses of human scalp identify gene-regulatory programs and critical cell types for hair and skin diseases. Nat Genet 2023; 55:1288-1300. [PMID: 37500727 PMCID: PMC11190942 DOI: 10.1038/s41588-023-01445-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 06/17/2023] [Indexed: 07/29/2023]
Abstract
Genome-wide association studies have identified many loci associated with hair and skin disease, but identification of causal variants requires deciphering of gene-regulatory networks in relevant cell types. We generated matched single-cell chromatin profiles and transcriptomes from scalp tissue from healthy controls and patients with alopecia areata, identifying diverse cell types of the hair follicle niche. By interrogating these datasets at multiple levels of cellular resolution, we infer 50-100% more enhancer-gene links than previous approaches and show that aggregate enhancer accessibility for highly regulated genes predicts expression. We use these gene-regulatory maps to prioritize cell types, genes and causal variants implicated in the pathobiology of androgenetic alopecia (AGA), eczema and other complex traits. AGA genome-wide association studies signals are enriched in dermal papilla regulatory regions, supporting the role of these cells as drivers of AGA pathogenesis. Finally, we train machine learning models to nominate single-nucleotide polymorphisms that affect gene expression through disruption of transcription factor binding, predicting candidate functional single-nucleotide polymorphism for AGA and eczema.
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Affiliation(s)
| | - Chen Wang
- Department of Dermatology, School of Medicine, Stanford University, Stanford, CA, USA
- Division of Dermatology, Department of Medicine, Santa Clara Valley Medical Center, San Jose, CA, USA
- Institute of Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA, USA
| | - Justin M Ko
- Department of Dermatology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Eon J Rios
- Department of Dermatology, School of Medicine, Stanford University, Stanford, CA, USA
- Division of Dermatology, Department of Medicine, Santa Clara Valley Medical Center, San Jose, CA, USA
| | - Sumaira Z Aasi
- Department of Dermatology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Mark M Davis
- Institute of Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA, USA
- Department of Microbiology and Immunology, School of Medicine, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, School of Medicine, Stanford University, Stanford, CA, USA
| | - Anthony E Oro
- Department of Dermatology, School of Medicine, Stanford University, Stanford, CA, USA
- Program in Epithelial Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - William J Greenleaf
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Applied Physics, Stanford University, Stanford, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
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181
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Armendariz DA, Sundarrajan A, Hon GC. Breaking enhancers to gain insights into developmental defects. eLife 2023; 12:e88187. [PMID: 37497775 PMCID: PMC10374278 DOI: 10.7554/elife.88187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 07/19/2023] [Indexed: 07/28/2023] Open
Abstract
Despite ground-breaking genetic studies that have identified thousands of risk variants for developmental diseases, how these variants lead to molecular and cellular phenotypes remains a gap in knowledge. Many of these variants are non-coding and occur at enhancers, which orchestrate key regulatory programs during development. The prevailing paradigm is that non-coding variants alter the activity of enhancers, impacting gene expression programs, and ultimately contributing to disease risk. A key obstacle to progress is the systematic functional characterization of non-coding variants at scale, especially since enhancer activity is highly specific to cell type and developmental stage. Here, we review the foundational studies of enhancers in developmental disease and current genomic approaches to functionally characterize developmental enhancers and their variants at scale. In the coming decade, we anticipate systematic enhancer perturbation studies to link non-coding variants to molecular mechanisms, changes in cell state, and disease phenotypes.
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Affiliation(s)
- Daniel A Armendariz
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
| | - Anjana Sundarrajan
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
| | - Gary C Hon
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
- Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, United States
- Lyda Hill Department of Bioinformatics, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, United States
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182
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Zhu C, Baumgarten N, Wu M, Wang Y, Das AP, Kaur J, Ardakani FB, Duong TT, Pham MD, Duda M, Dimmeler S, Yuan T, Schulz MH, Krishnan J. CVD-associated SNPs with regulatory potential reveal novel non-coding disease genes. Hum Genomics 2023; 17:69. [PMID: 37491351 PMCID: PMC10369730 DOI: 10.1186/s40246-023-00513-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 07/12/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) appearing in non-coding genomic regions in CVDs. The SNPs may alter gene expression by modifying transcription factor (TF) binding sites and lead to functional consequences in cardiovascular traits or diseases. To understand the underlying molecular mechanisms, it is crucial to identify which variations are involved and how they affect TF binding. METHODS The SNEEP (SNP exploration and analysis using epigenomics data) pipeline was used to identify regulatory SNPs, which alter the binding behavior of TFs and link GWAS SNPs to their potential target genes for six CVDs. The human-induced pluripotent stem cells derived cardiomyocytes (hiPSC-CMs), monoculture cardiac organoids (MCOs) and self-organized cardiac organoids (SCOs) were used in the study. Gene expression, cardiomyocyte size and cardiac contractility were assessed. RESULTS By using our integrative computational pipeline, we identified 1905 regulatory SNPs in CVD GWAS data. These were associated with hundreds of genes, half of them non-coding RNAs (ncRNAs), suggesting novel CVD genes. We experimentally tested 40 CVD-associated non-coding RNAs, among them RP11-98F14.11, RPL23AP92, IGBP1P1, and CTD-2383I20.1, which were upregulated in hiPSC-CMs, MCOs and SCOs under hypoxic conditions. Further experiments showed that IGBP1P1 depletion rescued expression of hypertrophic marker genes, reduced hypoxia-induced cardiomyocyte size and improved hypoxia-reduced cardiac contractility in hiPSC-CMs and MCOs. CONCLUSIONS IGBP1P1 is a novel ncRNA with key regulatory functions in modulating cardiomyocyte size and cardiac function in our disease models. Our data suggest ncRNA IGBP1P1 as a potential therapeutic target to improve cardiac function in CVDs.
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Affiliation(s)
- Chaonan Zhu
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany
- Cardio-Pulmonary Institute, Goethe University Hospital, 60590, Frankfurt Am Main, Germany
| | - Nina Baumgarten
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany
- German Center for Cardiovascular Research, Partner Site Rhein-Main, 60590, Frankfurt Am Main, Germany
- Cardio-Pulmonary Institute, Goethe University Hospital, 60590, Frankfurt Am Main, Germany
| | - Meiqian Wu
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany
| | - Yue Wang
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany
| | - Arka Provo Das
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany
- Cardio-Pulmonary Institute, Goethe University Hospital, 60590, Frankfurt Am Main, Germany
| | - Jaskiran Kaur
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany
| | - Fatemeh Behjati Ardakani
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany
- German Center for Cardiovascular Research, Partner Site Rhein-Main, 60590, Frankfurt Am Main, Germany
- Cardio-Pulmonary Institute, Goethe University Hospital, 60590, Frankfurt Am Main, Germany
| | - Thanh Thuy Duong
- Genome Biologics, Theodor-Stern-Kai 7, 60590, Frankfurt Am Main, Germany
| | - Minh Duc Pham
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany
- Cardio-Pulmonary Institute, Goethe University Hospital, 60590, Frankfurt Am Main, Germany
- Department of Medicine III, Cardiology/Angiology/ Nephrology, Goethe University Hospital, Frankfurt, Germany
- Genome Biologics, Theodor-Stern-Kai 7, 60590, Frankfurt Am Main, Germany
| | - Maria Duda
- Genome Biologics, Theodor-Stern-Kai 7, 60590, Frankfurt Am Main, Germany
| | - Stefanie Dimmeler
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany
- German Center for Cardiovascular Research, Partner Site Rhein-Main, 60590, Frankfurt Am Main, Germany
- Cardio-Pulmonary Institute, Goethe University Hospital, 60590, Frankfurt Am Main, Germany
| | - Ting Yuan
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany.
- Cardio-Pulmonary Institute, Goethe University Hospital, 60590, Frankfurt Am Main, Germany.
- Department of Medicine III, Cardiology/Angiology/ Nephrology, Goethe University Hospital, Frankfurt, Germany.
| | - Marcel H Schulz
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany.
- German Center for Cardiovascular Research, Partner Site Rhein-Main, 60590, Frankfurt Am Main, Germany.
- Cardio-Pulmonary Institute, Goethe University Hospital, 60590, Frankfurt Am Main, Germany.
| | - Jaya Krishnan
- Institute for Cardiovascular Regeneration, Goethe University, 60590, Frankfurt Am Main, Germany.
- German Center for Cardiovascular Research, Partner Site Rhein-Main, 60590, Frankfurt Am Main, Germany.
- Cardio-Pulmonary Institute, Goethe University Hospital, 60590, Frankfurt Am Main, Germany.
- Department of Medicine III, Cardiology/Angiology/ Nephrology, Goethe University Hospital, Frankfurt, Germany.
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183
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Shevade K, Peddada S, Mader K, Przybyla L. Functional genomics in stem cell models: considerations and applications. Front Cell Dev Biol 2023; 11:1236553. [PMID: 37554308 PMCID: PMC10404852 DOI: 10.3389/fcell.2023.1236553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 07/13/2023] [Indexed: 08/10/2023] Open
Abstract
Protocols to differentiate human pluripotent stem cells have advanced in terms of cell type specificity and tissue-level complexity over the past 2 decades, which has facilitated human disease modeling in the most relevant cell types. The ability to generate induced PSCs (iPSCs) from patients further enables the study of disease mutations in an appropriate cellular context to reveal the mechanisms that underlie disease etiology and progression. As iPSC-derived disease models have improved in robustness and scale, they have also been adopted more widely for use in drug screens to discover new therapies and therapeutic targets. Advancement in genome editing technologies, in particular the discovery of CRISPR-Cas9, has further allowed for rapid development of iPSCs containing disease-causing mutations. CRISPR-Cas9 technologies have now evolved beyond creating single gene edits, aided by the fusion of inhibitory (CRISPRi) or activation (CRISPRa) domains to a catalytically dead Cas9 protein, enabling inhibition or activation of endogenous gene loci. These tools have been used in CRISPR knockout, CRISPRi, or CRISPRa screens to identify genetic modifiers that synergize or antagonize with disease mutations in a systematic and unbiased manner, resulting in identification of disease mechanisms and discovery of new therapeutic targets to accelerate drug discovery research. However, many technical challenges remain when applying large-scale functional genomics approaches to differentiated PSC populations. Here we review current technologies in the field of iPSC disease modeling and CRISPR-based functional genomics screens and practical considerations for implementation across a range of modalities, applications, and disease areas, as well as explore CRISPR screens that have been performed in iPSC models to-date and the insights and therapies these screens have produced.
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Affiliation(s)
- Kaivalya Shevade
- Laboratory for Genomics Research, San Francisco, CA, United States
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, United States
| | - Sailaja Peddada
- Laboratory for Genomics Research, San Francisco, CA, United States
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, United States
| | - Karl Mader
- Laboratory for Genomics Research, San Francisco, CA, United States
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, United States
| | - Laralynne Przybyla
- Laboratory for Genomics Research, San Francisco, CA, United States
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, United States
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184
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The Impact of Genomic Variation on Function (IGVF) Consortium. ARXIV 2023:arXiv:2307.13708v1. [PMID: 37547663 PMCID: PMC10402186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Our genomes influence nearly every aspect of human biology from molecular and cellular functions to phenotypes in health and disease. Human genetics studies have now associated hundreds of thousands of differences in our DNA sequence ("genomic variation") with disease risk and other phenotypes, many of which could reveal novel mechanisms of human biology and uncover the basis of genetic predispositions to diseases, thereby guiding the development of new diagnostics and therapeutics. Yet, understanding how genomic variation alters genome function to influence phenotype has proven challenging. To unlock these insights, we need a systematic and comprehensive catalog of genome function and the molecular and cellular effects of genomic variants. Toward this goal, the Impact of Genomic Variation on Function (IGVF) Consortium will combine approaches in single-cell mapping, genomic perturbations, and predictive modeling to investigate the relationships among genomic variation, genome function, and phenotypes. Through systematic comparisons and benchmarking of experimental and computational methods, we aim to create maps across hundreds of cell types and states describing how coding variants alter protein activity, how noncoding variants change the regulation of gene expression, and how both coding and noncoding variants may connect through gene regulatory and protein interaction networks. These experimental data, computational predictions, and accompanying standards and pipelines will be integrated into an open resource that will catalyze community efforts to explore genome function and the impact of genetic variation on human biology and disease across populations.
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185
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Zhao X, Song L, Yang A, Zhang Z, Zhang J, Yang YT, Zhao XM. Prioritizing genes associated with brain disorders by leveraging enhancer-promoter interactions in diverse neural cells and tissues. Genome Med 2023; 15:56. [PMID: 37488639 PMCID: PMC10364416 DOI: 10.1186/s13073-023-01210-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 07/10/2023] [Indexed: 07/26/2023] Open
Abstract
BACKGROUND Prioritizing genes that underlie complex brain disorders poses a considerable challenge. Despite previous studies have found that they shared symptoms and heterogeneity, it remained difficult to systematically identify the risk genes associated with them. METHODS By using the CAGE (Cap Analysis of Gene Expression) read alignment files for 439 human cell and tissue types (including primary cells, tissues and cell lines) from FANTOM5 project, we predicted enhancer-promoter interactions (EPIs) of 439 cell and tissue types in human, and examined their reliability. Then we evaluated the genetic heritability of 17 diverse brain disorders and behavioral-cognitive phenotypes in each neural cell type, brain region, and developmental stage. Furthermore, we prioritized genes associated with brain disorders and phenotypes by leveraging the EPIs in each neural cell and tissue type, and analyzed their pleiotropy and functionality for different categories of disorders and phenotypes. Finally, we characterized the spatiotemporal expression dynamics of these associated genes in cells and tissues. RESULTS We found that identified EPIs showed activity specificity and network aggregation in cell and tissue types, and enriched TF binding in neural cells played key roles in synaptic plasticity and nerve cell development, i.e., EGR1 and SOX family. We also discovered that most neurological disorders exhibit heritability enrichment in neural stem cells and astrocytes, while psychiatric disorders and behavioral-cognitive phenotypes exhibit enrichment in neurons. Furthermore, our identified genes recapitulated well-known risk genes, which exhibited widespread pleiotropy between psychiatric disorders and behavioral-cognitive phenotypes (i.e., FOXP2), and indicated expression specificity in neural cell types, brain regions, and developmental stages associated with disorders and phenotypes. Importantly, we showed the potential associations of brain disorders with brain regions and developmental stages that have not been well studied. CONCLUSIONS Overall, our study characterized the gene-enhancer regulatory networks and genetic mechanisms in the human neural cells and tissues, and illustrated the value of reanalysis of publicly available genomic datasets.
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Affiliation(s)
- Xingzhong Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai, 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China
| | - Liting Song
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai, 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China
| | - Anyi Yang
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai, 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China
| | - Zichao Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai, 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China
| | - Jinglong Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai, 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China
| | - Yucheng T Yang
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai, 200433, China.
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China.
| | - Xing-Ming Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai, 200433, China.
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China.
- State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, 200032, China.
- Internatioal Human Phenome Institutes (Shanghai), Shanghai, 200433, China.
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186
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Murphy D, Salataj E, Di Giammartino DC, Rodriguez-Hernaez J, Kloetgen A, Garg V, Char E, Uyehara CM, Ee LS, Lee U, Stadtfeld M, Hadjantonakis AK, Tsirigos A, Polyzos A, Apostolou E. Systematic mapping and modeling of 3D enhancer-promoter interactions in early mouse embryonic lineages reveal regulatory principles that determine the levels and cell-type specificity of gene expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.19.549714. [PMID: 37577543 PMCID: PMC10422694 DOI: 10.1101/2023.07.19.549714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Mammalian embryogenesis commences with two pivotal and binary cell fate decisions that give rise to three essential lineages, the trophectoderm (TE), the epiblast (EPI) and the primitive endoderm (PrE). Although key signaling pathways and transcription factors that control these early embryonic decisions have been identified, the non-coding regulatory elements via which transcriptional regulators enact these fates remain understudied. To address this gap, we have characterized, at a genome-wide scale, enhancer activity and 3D connectivity in embryo-derived stem cell lines that represent each of the early developmental fates. We observed extensive enhancer remodeling and fine-scale 3D chromatin rewiring among the three lineages, which strongly associate with transcriptional changes, although there are distinct groups of genes that are irresponsive to topological changes. In each lineage, a high degree of connectivity or "hubness" positively correlates with levels of gene expression and enriches for cell-type specific and essential genes. Genes within 3D hubs also show a significantly stronger probability of coregulation across lineages, compared to genes in linear proximity or within the same contact domains. By incorporating 3D chromatin features, we build a novel predictive model for transcriptional regulation (3D-HiChAT), which outperformed models that use only 1D promoter or proximal variables in predicting levels and cell-type specificity of gene expression. Using 3D-HiChAT, we performed genome-wide in silico perturbations to nominate candidate functional enhancers and hubs in each cell lineage, and with CRISPRi experiments we validated several novel enhancers that control expression of one or more genes in their respective lineages. Our study comprehensively identifies 3D regulatory hubs associated with the earliest mammalian lineages and describes their relationship to gene expression and cell identity, providing a framework to understand lineage-specific transcriptional behaviors.
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Affiliation(s)
- Dylan Murphy
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Eralda Salataj
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Dafne Campigli Di Giammartino
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
- 3D Chromatin Conformation and RNA genomics laboratory, Instituto Italiano di Tecnologia (IIT), Center for Human Technologies (CHT), Genova, Italy (current affiliation)
| | - Javier Rodriguez-Hernaez
- Department of Pathology, New York University Langone Health, New York, NY 10016, USA
- Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY 10016, USA
| | - Andreas Kloetgen
- Department of Pathology, New York University Langone Health, New York, NY 10016, USA
- Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY 10016, USA
| | - Vidur Garg
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Biochemistry Cell and Molecular Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY 10065, USA
| | - Erin Char
- Tri-Institutional Training Program in Computational Biology and Medicine, Weill Cornell Medical College, New York, 10065, New York, USA
| | - Christopher M. Uyehara
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Ly-sha Ee
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - UkJin Lee
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Matthias Stadtfeld
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Anna-Katerina Hadjantonakis
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Biochemistry Cell and Molecular Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY 10065, USA
| | - Aristotelis Tsirigos
- Department of Pathology, New York University Langone Health, New York, NY 10016, USA
- Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY 10016, USA
| | - Alexander Polyzos
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Effie Apostolou
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
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187
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Powell SK, Liao W, O’Shea C, Kammourh S, Ghorbani S, Rigat R, Elahi R, Deans PJM, Le DJ, Agarwal P, Seow WQ, Wang KC, Akbarian S, Brennand KJ. Schizophrenia Risk Mapping and Functional Engineering of the 3D Genome in Three Neuronal Subtypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.17.549339. [PMID: 37502907 PMCID: PMC10370055 DOI: 10.1101/2023.07.17.549339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Common variants associated with schizophrenia are concentrated in non-coding regulatory sequences, but their precise target genes are context-dependent and impacted by cell-type-specific three-dimensional spatial chromatin organization. Here, we map long-range chromosomal conformations in isogenic human dopaminergic, GABAergic, and glutamatergic neurons to track developmentally programmed shifts in the regulatory activity of schizophrenia risk loci. Massive repressive compartmentalization, concomitant with the emergence of hundreds of neuron-specific multi-valent chromatin architectural stripes, occurs during neuronal differentiation, with genes interconnected to genetic risk loci through these long-range chromatin structures differing in their biological roles from genes more proximal to sequences conferring heritable risk. Chemically induced CRISPR-guided chromosomal loop-engineering for the proximal risk gene SNAP91 and distal risk gene BHLHE22 profoundly alters synaptic development and functional activity. Our findings highlight the large-scale cell-type-specific reorganization of chromosomal conformations at schizophrenia risk loci during neurodevelopment and establish a causal link between risk-associated gene-regulatory loop structures and neuronal function.
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Affiliation(s)
- Samuel K. Powell
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Will Liao
- New York Genome Center, New York, NY, 10029
| | - Callan O’Shea
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Sarah Kammourh
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Sadaf Ghorbani
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Raymond Rigat
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Rahat Elahi
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - PJ Michael Deans
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Derek J. Le
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
- Cancer Biology Program, Stanford University School of Medicine, Stanford, California, 94305, USA
| | - Poonam Agarwal
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
| | - Wei Qiang Seow
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
| | - Kevin C. Wang
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
- Cancer Biology Program, Stanford University School of Medicine, Stanford, California, 94305, USA
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, California, 94304, USA
| | - Schahram Akbarian
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Kristen J. Brennand
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
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188
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Koike Y, Takahata M, Nakajima M, Otomo N, Suetsugu H, Liu X, Endo T, Imagama S, Kobayashi K, Kaito T, Kato S, Kawaguchi Y, Kanayama M, Sakai H, Tsuji T, Miyamoto T, Inose H, Yoshii T, Kashii M, Nakashima H, Ando K, Taniguchi Y, Takeuchi K, Ito S, Tomizuka K, Hikino K, Iwasaki Y, Kamatani Y, Maeda S, Nakajima H, Mori K, Seichi A, Fujibayashi S, Kanchiku T, Watanabe K, Tanaka T, Kida K, Kobayashi S, Takahashi M, Yamada K, Takuwa H, Lu HF, Niida S, Ozaki K, Momozawa Y, Yamazaki M, Okawa A, Matsumoto M, Iwasaki N, Terao C, Ikegawa S. Genetic insights into ossification of the posterior longitudinal ligament of the spine. eLife 2023; 12:e86514. [PMID: 37461309 DOI: 10.7554/elife.86514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 05/22/2023] [Indexed: 07/20/2023] Open
Abstract
Ossification of the posterior longitudinal ligament of the spine (OPLL) is an intractable disease leading to severe neurological deficits. Its etiology and pathogenesis are primarily unknown. The relationship between OPLL and comorbidities, especially type 2 diabetes (T2D) and high body mass index (BMI), has been the focus of attention; however, no trait has been proven to have a causal relationship. We conducted a meta-analysis of genome-wide association studies (GWASs) using 22,016 Japanese individuals and identified 14 significant loci, 8 of which were previously unreported. We then conducted a gene-based association analysis and a transcriptome-wide Mendelian randomization approach and identified three candidate genes for each. Partitioning heritability enrichment analyses observed significant enrichment of the polygenic signals in the active enhancers of the connective/bone cell group, especially H3K27ac in chondrogenic differentiation cells, as well as the immune/hematopoietic cell group. Single-cell RNA sequencing of Achilles tendon cells from a mouse Achilles tendon ossification model confirmed the expression of genes in GWAS and post-GWAS analyses in mesenchymal and immune cells. Genetic correlations with 96 complex traits showed positive correlations with T2D and BMI and a negative correlation with cerebral aneurysm. Mendelian randomization analysis demonstrated a significant causal effect of increased BMI and high bone mineral density on OPLL. We evaluated the clinical images in detail and classified OPLL into cervical, thoracic, and the other types. GWAS subanalyses identified subtype-specific signals. A polygenic risk score for BMI demonstrated that the effect of BMI was particularly strong in thoracic OPLL. Our study provides genetic insight into the etiology and pathogenesis of OPLL and is expected to serve as a basis for future treatment development.
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Affiliation(s)
- Yoshinao Koike
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Masahiko Takahata
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Masahiro Nakajima
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
| | - Nao Otomo
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Department of Orthopedic Surgery, Keio University School of Medicine, Nagoya, Japan
| | - Hiroyuki Suetsugu
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Department of Orthopaedic Surgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Tsutomu Endo
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Shiro Imagama
- Department of Orthopedics, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kazuyoshi Kobayashi
- Department of Orthopedics, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Takashi Kaito
- Department of Orthopaedic Surgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Satoshi Kato
- Department of Orthopaedic Surgery, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | | | - Masahiro Kanayama
- Department of Orthopedics, Hakodate Central General Hospital, Hakodate, Japan
| | - Hiroaki Sakai
- Department of Orthopaedic Surgery, Spinal Injuries Center, Iizuka, Japan
| | - Takashi Tsuji
- Department of Orthopedic Surgery, Keio University School of Medicine, Nagoya, Japan
- Department of Spine and Spinal Cord Surgery, Fujita Health University, Toyoake, Japan
| | - Takeshi Miyamoto
- Department of Orthopedic Surgery, Keio University School of Medicine, Nagoya, Japan
- Department of Orthopedic Surgery, Kumamoto University, Kumamoto, Japan
| | - Hiroyuki Inose
- Department of Orthopaedic Surgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Toshitaka Yoshii
- Department of Orthopaedic Surgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Masafumi Kashii
- Department of Orthopaedic Surgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Hiroaki Nakashima
- Department of Orthopedics, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kei Ando
- Department of Orthopedics, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yuki Taniguchi
- Department of Orthopaedic Surgery, Faculty of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kazuhiro Takeuchi
- Department of Orthopaedic Surgery, National Okayama Medical Center, Okayama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Department of Orthopedic Surgery, Shimane University Faculty of Medicine, Izumo, Japan
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Yusuke Iwasaki
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Shingo Maeda
- Department of Bone and Joint Medicine, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan
| | - Hideaki Nakajima
- Department of Orthopaedics and Rehabilitation Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
| | - Kanji Mori
- Department of Orthopaedic Surgery, Shiga University of Medical Science, Otsu, Japan
| | - Atsushi Seichi
- Department of Orthopedics, Jichi Medical University, Shimotsuke, Japan
| | - Shunsuke Fujibayashi
- Department of Orthopaedic Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tsukasa Kanchiku
- Department of Orthopedic Surgery, Yamaguchi University Graduate School of Medicine, Ube, Japan
| | - Kei Watanabe
- Department of Orthopaedic Surgery, Niigata University Medical and Dental General Hospital, Nankoku, Japan
| | - Toshihiro Tanaka
- Department of Orthopaedic Surgery, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Kazunobu Kida
- Department of Orthopaedic Surgery, Kochi Medical School, Nankoku, Japan
| | - Sho Kobayashi
- Department of Orthopaedic Surgery, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Masahito Takahashi
- Department of Orthopaedic Surgery, Kyorin University School of Medicine, Tokyo, Japan
| | - Kei Yamada
- Department of Orthopaedic Surgery, Kurume University School of Medicine, Obu, Japan
| | - Hiroshi Takuwa
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Department of Orthopedic Surgery, Shimane University Faculty of Medicine, Izumo, Japan
| | - Hsing-Fang Lu
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Million-Person Precision Medicine Initiative, China Medical University Hospital, Taichung, Taiwan
| | - Shumpei Niida
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Masashi Yamazaki
- Department of Orthopaedic Surgery, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Atsushi Okawa
- Department of Orthopaedic Surgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Morio Matsumoto
- Department of Orthopedic Surgery, Keio University School of Medicine, Nagoya, Japan
| | - Norimasa Iwasaki
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
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189
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Dincer TU, Ernst J. Integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.14.549056. [PMID: 37503240 PMCID: PMC10369970 DOI: 10.1101/2023.07.14.549056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
We introduce ChromActivity, a computational framework for predicting and annotating regulatory activity across the genome through integration of multiple epigenomic maps and various functional characterization datasets. ChromActivity generates genomewide predictions of regulatory activity associated with each functional characterization dataset across many cell types based on available epigenomic data. It then for each cell type produces (1) ChromScoreHMM genome annotations based on the combinatorial and spatial patterns within these predictions and (2) ChromScore tracks of overall predicted regulatory activity. ChromActivity provides a resource for analyzing and interpreting the human regulatory genome across diverse cell types.
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Affiliation(s)
- Tevfik Umut Dincer
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, 90095, USA
- Department of Biological Chemistry, University of California, Los Angeles, CA, 90095, USA
| | - Jason Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, 90095, USA
- Department of Biological Chemistry, University of California, Los Angeles, CA, 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at University of California, Los Angeles, CA, 90095, USA
- Computer Science Department, University of California, Los Angeles, CA, 90095, USA
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, CA, 90095, USA
- Department of Computational Medicine, University of California, Los Angeles, CA, 90095, USA
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190
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Barnett KR, Mobley RJ, Diedrich JD, Bergeron BP, Bhattarai KR, Yang W, Crews KR, Manring CS, Jabbour E, Paietta E, Litzow MR, Kornblau SM, Stock W, Inaba H, Jeha S, Pui CH, Mullighan CG, Relling MV, Yang JJ, Evans WE, Savic D. Epigenomic mapping in B-cell acute lymphoblastic leukemia identifies transcriptional regulators and noncoding variants promoting distinct chromatin architectures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.14.528493. [PMID: 36824825 PMCID: PMC9949063 DOI: 10.1101/2023.02.14.528493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
B-cell lineage acute lymphoblastic leukemia (B-ALL) is comprised of diverse molecular subtypes and while transcriptional and DNA methylation profiling of B-ALL subtypes has been extensively examined, the accompanying chromatin landscape is not well characterized for many subtypes. We therefore mapped chromatin accessibility using ATAC-seq for 10 B-ALL molecular subtypes in primary ALL cells from 154 patients. Comparisons with B-cell progenitors identified candidate B-ALL cell-of-origin and AP-1-associated cis-regulatory rewiring in B-ALL. Cis-regulatory rewiring promoted B-ALL-specific gene regulatory networks impacting oncogenic signaling pathways that perturb normal B-cell development. We also identified that over 20% of B-ALL accessible chromatin sites exhibit strong subtype enrichment, with transcription factor (TF) footprint profiling identifying candidate TFs that maintain subtype-specific chromatin architectures. Over 9000 inherited genetic variants were further uncovered that contribute to variability in chromatin accessibility among individual patient samples. Overall, our data suggest that distinct chromatin architectures are driven by diverse TFs and inherited genetic variants which promote unique gene regulatory networks that contribute to transcriptional differences among B-ALL subtypes.
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Affiliation(s)
- Kelly R. Barnett
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Robert J. Mobley
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Jonathan D. Diedrich
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Brennan P. Bergeron
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Kashi Raj Bhattarai
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Wenjian Yang
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Kristine R. Crews
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Christopher S. Manring
- Alliance Hematologic Malignancy Biorepository; Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus, OH 43210, USA
| | - Elias Jabbour
- Department of Leukemia, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA
| | - Elisabeth Paietta
- Department of Oncology, Montefiore Medical Center, Bronx, NY 10467, USA
| | - Mark R. Litzow
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Steven M. Kornblau
- Department of Leukemia, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA
| | - Wendy Stock
- University of Chicago Comprehensive Cancer Center, Chicago, IL 60637, USA
| | - Hiroto Inaba
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Oncology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Sima Jeha
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Oncology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Ching-Hon Pui
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Oncology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Charles G. Mullighan
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Mary V. Relling
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Jun J. Yang
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN 38105, USA
| | - William E. Evans
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Daniel Savic
- Hematological Malignancies Program, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN 38105, USA
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191
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Xie F, Armand EJ, Yao Z, Liu H, Bartlett A, Behrens MM, Li YE, Lucero JD, Luo C, Nery JR, Pinto-Duarte A, Poirion OB, Preissl S, Rivkin AC, Tasic B, Zeng H, Ren B, Ecker JR, Mukamel EA. Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes. CELL GENOMICS 2023; 3:100342. [PMID: 37492103 PMCID: PMC10363915 DOI: 10.1016/j.xgen.2023.100342] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 03/09/2023] [Accepted: 05/17/2023] [Indexed: 07/27/2023]
Abstract
Single-cell sequencing could help to solve the fundamental challenge of linking millions of cell-type-specific enhancers with their target genes. However, this task is confounded by patterns of gene co-expression in much the same way that genetic correlation due to linkage disequilibrium confounds fine-mapping in genome-wide association studies (GWAS). We developed a non-parametric permutation-based procedure to establish stringent statistical criteria to control the risk of false-positive associations in enhancer-gene association studies (EGAS). We applied our procedure to large-scale transcriptome and epigenome data from multiple tissues and species, including the mouse and human brain, to predict enhancer-gene associations genome wide. We tested the functional validity of our predictions by comparing them with chromatin conformation data and causal enhancer perturbation experiments. Our study shows how controlling for gene co-expression enables robust enhancer-gene linkage using single-cell sequencing data.
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Affiliation(s)
- Fangming Xie
- Department of Physics, University of California San Diego, La Jolla, CA 92037, USA
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Ethan J. Armand
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92037, USA
| | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - M. Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Yang Eric Li
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA 92037, USA
| | - Jacinta D. Lucero
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Chongyuan Luo
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Joseph R. Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Antonio Pinto-Duarte
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Olivier B. Poirion
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA 92037, USA
- The Jackson Laboratory, Farmington, CT, USA
| | - Sebastian Preissl
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA 92037, USA
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Angeline C. Rivkin
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Bosiljka Tasic
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA 92037, USA
| | - Joseph R. Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Eran A. Mukamel
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92037, USA
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192
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Liang L, Cao C, Ji L, Cai Z, Wang D, Ye R, Chen J, Yu X, Zhou J, Bai Z, Wang R, Yang X, Zhu P, Xue Y. Complementary Alu sequences mediate enhancer-promoter selectivity. Nature 2023:10.1038/s41586-023-06323-x. [PMID: 37438529 DOI: 10.1038/s41586-023-06323-x] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 06/14/2023] [Indexed: 07/14/2023]
Abstract
Enhancers determine spatiotemporal gene expression programs by engaging with long-range promoters1-4. However, it remains unknown how enhancers find their cognate promoters. We recently developed a RNA in situ conformation sequencing technology to identify enhancer-promoter connectivity using pairwise interacting enhancer RNAs and promoter-derived noncoding RNAs5,6. Here we apply this technology to generate high-confidence enhancer-promoter RNA interaction maps in six additional cell lines. Using these maps, we discover that 37.9% of the enhancer-promoter RNA interaction sites are overlapped with Alu sequences. These pairwise interacting Alu and non-Alu RNA sequences tend to be complementary and potentially form duplexes. Knockout of Alu elements compromises enhancer-promoter looping, whereas Alu insertion or CRISPR-dCasRx-mediated Alu tethering to unregulated promoter RNAs can create new loops to homologous enhancers. Mapping 535,404 noncoding risk variants back to the enhancer-promoter RNA interaction maps enabled us to construct variant-to-function maps for interpreting their molecular functions, including 15,318 deletions or insertions in 11,677 Alu elements that affect 6,497 protein-coding genes. We further demonstrate that polymorphic Alu insertion at the PTK2 enhancer can promote tumorigenesis. Our study uncovers a principle for determining enhancer-promoter pairing specificity and provides a framework to link noncoding risk variants to their molecular functions.
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Affiliation(s)
- Liang Liang
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Changchang Cao
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Lei Ji
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Zhaokui Cai
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Di Wang
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Rong Ye
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Juan Chen
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Xiaohua Yu
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Jie Zhou
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhibo Bai
- School of Life Sciences, Henan Normal University, Xinxiang, China
| | - Ruoyan Wang
- School of Life Sciences, Henan Normal University, Xinxiang, China
| | - Xianguang Yang
- School of Life Sciences, Henan Normal University, Xinxiang, China
| | - Ping Zhu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yuanchao Xue
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
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193
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Barbosa IAM, Gopalakrishnan R, Mercan S, Mourikis TP, Martin T, Wengert S, Sheng C, Ji F, Lopes R, Knehr J, Altorfer M, Lindeman A, Russ C, Naumann U, Golji J, Sprouffske K, Barys L, Tordella L, Schübeler D, Schmelzle T, Galli GG. Cancer lineage-specific regulation of YAP responsive elements revealed through large-scale functional epigenomic screens. Nat Commun 2023; 14:3907. [PMID: 37400441 DOI: 10.1038/s41467-023-39527-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 06/14/2023] [Indexed: 07/05/2023] Open
Abstract
YAP is a key transcriptional co-activator of TEADs, it regulates cell growth and is frequently activated in cancer. In Malignant Pleural Mesothelioma (MPM), YAP is activated by loss-of-function mutations in upstream components of the Hippo pathway, while, in Uveal Melanoma (UM), YAP is activated in a Hippo-independent manner. To date, it is unclear if and how the different oncogenic lesions activating YAP impact its oncogenic program, which is particularly relevant for designing selective anti-cancer therapies. Here we show that, despite YAP being essential in both MPM and UM, its interaction with TEAD is unexpectedly dispensable in UM, limiting the applicability of TEAD inhibitors in this cancer type. Systematic functional interrogation of YAP regulatory elements in both cancer types reveals convergent regulation of broad oncogenic drivers in both MPM and UM, but also strikingly selective programs. Our work reveals unanticipated lineage-specific features of the YAP regulatory network that provide important insights to guide the design of tailored therapeutic strategies to inhibit YAP signaling across different cancer types.
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Affiliation(s)
- Inês A M Barbosa
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Rajaraman Gopalakrishnan
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Cambridge, MA, USA
- Alltrna Inc., One Kendall Square, Cambridge, MA, USA
| | - Samuele Mercan
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Thanos P Mourikis
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Typhaine Martin
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Simon Wengert
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
- Helmholtz Pioneer Campus, Helmholtz Zentrum München GmbH German Research Center for Environmental Health, Neuherberg, Germany
| | - Caibin Sheng
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Fei Ji
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Rui Lopes
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
- Roche Pharmaceutical Research and Early Development, Basel, Switzerland
| | - Judith Knehr
- Chemical Biology and Therapeutics, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Marc Altorfer
- Chemical Biology and Therapeutics, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Alicia Lindeman
- Chemical Biology and Therapeutics, Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Carsten Russ
- Chemical Biology and Therapeutics, Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Ulrike Naumann
- Chemical Biology and Therapeutics, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Javad Golji
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Kathleen Sprouffske
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Louise Barys
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Luca Tordella
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Dirk Schübeler
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- Faculty of Sciences, University of Basel, Basel, Switzerland
| | - Tobias Schmelzle
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Giorgio G Galli
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland.
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194
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Rodríguez TC, Kwan S, Smith JL, Dadafarin S, Wu CH, Sontheimer EJ, Xue W. Multiomics characterization of mouse hepatoblastoma identifies yes-associated protein 1 target genes. Hepatology 2023; 78:58-71. [PMID: 35932276 PMCID: PMC10205091 DOI: 10.1002/hep.32713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 08/01/2022] [Accepted: 08/02/2022] [Indexed: 12/08/2022]
Abstract
BACKGROUND AND AIMS Hepatoblastoma (HB) is the most common primary liver malignancy in childhood and lacks targeted therapeutic options. We previously engineered, to our knowledge, the first yes-associated protein 1 (YAP1) S127A -inducible mouse model of HB, demonstrating tumor regression and redifferentiation after YAP1 withdrawal through genome-wide enhancer modulation. Probing accessibility, transcription, and YAP1 binding at regulatory elements in HB tumors may provide more insight into YAP1-driven tumorigenesis and expose exploitable vulnerabilities in HB. APPROACH AND RESULTS Using a multiomics approach, we integrated high-throughput transcriptome and chromatin profiling of our murine HB model to identify dynamic activity at candidate cis -regulatory elements (cCREs). We observed that 1301 of 305,596 cCREs exhibit "tumor-modified" (TM) accessibility in HB. We mapped 241 TM enhancers to corresponding genes using accessibility and histone H3K27Ac profiles. Anti-YAP1 cleavage under targets and tagmentation in tumors revealed 66 YAP1-bound TM cCRE/gene pairs, 31 of which decrease expression after YAP1 withdrawal. We validated the YAP1-dependent expression of a putative YAP1 target, Jun dimerization protein 2 (JDP2), in human HB cell lines using YAP1 and LATS1/2 small interfering RNA knockdown. We also confirmed YAP1-induced activity of the Jdp2 TM enhancer in vitro and discovered an analogous human enhancer in silico. Finally, we used transcription factor (TF) footprinting to identify putative YAP1 cofactors and characterize HB-specific TF activity genome wide. CONCLUSIONS Our chromatin-profiling techniques define the regulatory frameworks underlying HB and identify YAP1-regulated gene/enhancer pairs. JDP2 is an extensively validated target with YAP1-dependent expression in human HB cell lines and hepatic malignancies.
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Affiliation(s)
- Tomás C. Rodríguez
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605
| | - SuetYan Kwan
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605
| | - Jordan L. Smith
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605
| | | | - Chern-Horng Wu
- Division of Internal Medicine and Primary Care, Tufts Medical Center, 800 Washington, Boston, MA, 02111
| | - Erik J. Sontheimer
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605
| | - Wen Xue
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605
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195
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Guga S, Wang Y, Graham DC, Vyse TJ. A review of genetic risk in systemic lupus erythematosus. Expert Rev Clin Immunol 2023; 19:1247-1258. [PMID: 37496418 DOI: 10.1080/1744666x.2023.2240959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 05/10/2023] [Indexed: 07/28/2023]
Abstract
INTRODUCTION Systemic Lupus Erythematosus (SLE) is a complex multisystem autoimmune disease with a wide range of signs and symptoms in affected individuals. The utilization of genome-wide association study (GWAS) technology has led to an explosion in the number of genetic risk factors mapped for autoimmune diseases, including SLE. AREAS COVERED In this review, we summarize the more recent genetic risk loci mapped in SLE, which bring the total number of loci mapped to approximately 200. We review prioritization analyses of the associated variants and experimental validation of the putative causal variants. This includes the implementation of new bioinformatic techniques to align genomic and functional data and the use of transcriptomics with single-cell RNA-sequencing, CRISPR genome editing, and Massive Parallel Reporter Assays to analyze non-coding regulatory genetics. EXPERT OPINION Despite progress in identifying more genetic risk loci and variant-gene pairs for SLE, understanding its pathogenesis and applying findings clinically remains challenging. The polygenic risk score (PRS) has been used as an application of SLE genetics, but with limited performance in non-EUR populations. In the next few years, advancements in proteomics, post-translational modification estimation, and whole-genome sequencing will enhance disease understanding.
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Affiliation(s)
- Suri Guga
- Department of Medical & Molecular Genetics, King's College London, London, UK
| | - Yuxuan Wang
- Department of Medical & Molecular Genetics, King's College London, London, UK
| | | | - Timothy J Vyse
- Department of Medical & Molecular Genetics, King's College London, London, UK
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196
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Jia BB, Jussila A, Kern C, Zhu Q, Ren B. A spatial genome aligner for resolving chromatin architectures from multiplexed DNA FISH. Nat Biotechnol 2023; 41:1004-1017. [PMID: 36593410 PMCID: PMC10344783 DOI: 10.1038/s41587-022-01568-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 10/13/2022] [Indexed: 01/03/2023]
Abstract
Multiplexed fluorescence in situ hybridization (FISH) is a widely used approach for analyzing three-dimensional genome organization, but it is challenging to derive chromosomal conformations from noisy fluorescence signals, and tracing chromatin is not straightforward. Here we report a spatial genome aligner that parses true chromatin signal from noise by aligning signals to a DNA polymer model. Using genomic distances separating imaged loci, our aligner estimates spatial distances expected to separate loci on a polymer in three-dimensional space. Our aligner then evaluates the physical probability observed signals belonging to these loci are connected, thereby tracing chromatin structures. We demonstrate that this spatial genome aligner can efficiently model chromosome architectures from DNA FISH data across multiple scales and be used to predict chromosome ploidies de novo in interphase cells. Reprocessing of previous whole-genome chromosome tracing data with this method indicates the spatial aggregation of sister chromatids in S/G2 phase cells in asynchronous mouse embryonic stem cells and provides evidence for extranumerary chromosomes that remain tightly paired in postmitotic neurons of the adult mouse cortex.
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Affiliation(s)
- Bojing Blair Jia
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA
- Medical Scientist Training Program, University of California San Diego, La Jolla, CA, USA
| | - Adam Jussila
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Colin Kern
- Department of Cellular and Molecular Medicine, Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Quan Zhu
- Department of Cellular and Molecular Medicine, Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, Center for Epigenomics, University of California San Diego, La Jolla, CA, USA.
- Ludwig Institute for Cancer Research, La Jolla, CA, USA.
- Institute of Genomic Medicine, Moores Cancer Center, School of Medicine, University of California San Diego, La Jolla, CA, USA.
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197
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Kiryluk K, Sanchez-Rodriguez E, Zhou XJ, Zanoni F, Liu L, Mladkova N, Khan A, Marasa M, Zhang JY, Balderes O, Sanna-Cherchi S, Bomback AS, Canetta PA, Appel GB, Radhakrishnan J, Trimarchi H, Sprangers B, Cattran DC, Reich H, Pei Y, Ravani P, Galesic K, Maixnerova D, Tesar V, Stengel B, Metzger M, Canaud G, Maillard N, Berthoux F, Berthelot L, Pillebout E, Monteiro R, Nelson R, Wyatt RJ, Smoyer W, Mahan J, Samhar AA, Hidalgo G, Quiroga A, Weng P, Sreedharan R, Selewski D, Davis K, Kallash M, Vasylyeva TL, Rheault M, Chishti A, Ranch D, Wenderfer SE, Samsonov D, Claes DJ, Akchurin O, Goumenos D, Stangou M, Nagy J, Kovacs T, Fiaccadori E, Amoroso A, Barlassina C, Cusi D, Del Vecchio L, Battaglia GG, Bodria M, Boer E, Bono L, Boscutti G, Caridi G, Lugani F, Ghiggeri G, Coppo R, Peruzzi L, Esposito V, Esposito C, Feriozzi S, Polci R, Frasca G, Galliani M, Garozzo M, Mitrotti A, Gesualdo L, Granata S, Zaza G, Londrino F, Magistroni R, Pisani I, Magnano A, Marcantoni C, Messa P, Mignani R, Pani A, Ponticelli C, Roccatello D, Salvadori M, Salvi E, Santoro D, Gembillo G, Savoldi S, Spotti D, Zamboli P, Izzi C, Alberici F, Delbarba E, Florczak M, Krata N, Mucha K, Pączek L, Niemczyk S, Moszczuk B, Pańczyk-Tomaszewska M, Mizerska-Wasiak M, Perkowska-Ptasińska A, Bączkowska T, Durlik M, Pawlaczyk K, Sikora P, Zaniew M, Kaminska D, Krajewska M, Kuzmiuk-Glembin I, Heleniak Z, Bullo-Piontecka B, Liberek T, Dębska-Slizien A, Hryszko T, Materna-Kiryluk A, Miklaszewska M, Szczepańska M, Dyga K, Machura E, Siniewicz-Luzeńczyk K, Pawlak-Bratkowska M, Tkaczyk M, Runowski D, Kwella N, Drożdż D, Habura I, Kronenberg F, Prikhodina L, van Heel D, Fontaine B, Cotsapas C, Wijmenga C, Franke A, Annese V, Gregersen PK, Parameswaran S, Weirauch M, Kottyan L, Harley JB, Suzuki H, Narita I, Goto S, Lee H, Kim DK, Kim YS, Park JH, Cho B, Choi M, Van Wijk A, Huerta A, Ars E, Ballarin J, Lundberg S, Vogt B, Mani LY, Caliskan Y, Barratt J, Abeygunaratne T, Kalra PA, Gale DP, Panzer U, Rauen T, Floege J, Schlosser P, Ekici AB, Eckardt KU, Chen N, Xie J, Lifton RP, Loos RJF, Kenny EE, Ionita-Laza I, Köttgen A, Julian BA, Novak J, Scolari F, Zhang H, Gharavi AG. Genome-wide association analyses define pathogenic signaling pathways and prioritize drug targets for IgA nephropathy. Nat Genet 2023; 55:1091-1105. [PMID: 37337107 DOI: 10.1038/s41588-023-01422-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 05/05/2023] [Indexed: 06/21/2023]
Abstract
IgA nephropathy (IgAN) is a progressive form of kidney disease defined by glomerular deposition of IgA. Here we performed a genome-wide association study of 10,146 kidney-biopsy-diagnosed IgAN cases and 28,751 controls across 17 international cohorts. We defined 30 genome-wide significant risk loci explaining 11% of disease risk. A total of 16 loci were new, including TNFSF4/TNFSF18, REL, CD28, PF4V1, LY86, LYN, ANXA3, TNFSF8/TNFSF15, REEP3, ZMIZ1, OVOL1/RELA, ETS1, IGH, IRF8, TNFRSF13B and FCAR. The risk loci were enriched in gene orthologs causing abnormal IgA levels when genetically manipulated in mice. We also observed a positive genetic correlation between IgAN and serum IgA levels. High polygenic score for IgAN was associated with earlier onset of kidney failure. In a comprehensive functional annotation analysis of candidate causal genes, we observed convergence of biological candidates on a common set of inflammatory signaling pathways and cytokine ligand-receptor pairs, prioritizing potential new drug targets.
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Affiliation(s)
- Krzysztof Kiryluk
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA.
- Institute for Genomic Medicine, Columbia University, New York City, NY, USA.
| | - Elena Sanchez-Rodriguez
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
| | - Francesca Zanoni
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Lili Liu
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Nikol Mladkova
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Atlas Khan
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Maddalena Marasa
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Jun Y Zhang
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Olivia Balderes
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Simone Sanna-Cherchi
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
- Institute for Genomic Medicine, Columbia University, New York City, NY, USA
| | - Andrew S Bomback
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Pietro A Canetta
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Gerald B Appel
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Jai Radhakrishnan
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA
| | - Hernan Trimarchi
- Nephrology Service, Hospital Británico de Buenos Aires, Buenos Aires, Argentina
| | - Ben Sprangers
- Department of Microbiology and Immunology, Laboratory of Molecular Immunology, KU Leuven, Leuven, Belgium
- Division of Nephrology, University Hospitals Leuven, Leuven, Belgium
| | - Daniel C Cattran
- Department of Nephrology, University of Toronto, Toronto General Hospital, Toronto, Ontario, Canada
| | - Heather Reich
- Department of Nephrology, University of Toronto, Toronto General Hospital, Toronto, Ontario, Canada
| | - York Pei
- Department of Nephrology, University of Toronto, Toronto General Hospital, Toronto, Ontario, Canada
| | - Pietro Ravani
- Division of Nephrology, Department of Internal Medicine, University of Calgary, Calgary, Alberta, Canada
| | | | - Dita Maixnerova
- 1st Faculty of Medicine and General University Hospital, Charles University, Prague, Czech Republic
| | - Vladimir Tesar
- 1st Faculty of Medicine and General University Hospital, Charles University, Prague, Czech Republic
| | - Benedicte Stengel
- Centre for Research in Epidemiology and Population Health (CESP), Paris-Saclay University, Versailles Saint Quentin University, INSERM Clinical Epidemiology Team, Villejuif, France
| | - Marie Metzger
- Centre for Research in Epidemiology and Population Health (CESP), Paris-Saclay University, Versailles Saint Quentin University, INSERM Clinical Epidemiology Team, Villejuif, France
| | - Guillaume Canaud
- Université de Paris, Hôpital Necker-Enfants Malades, Paris, France
| | - Nicolas Maillard
- Nephrology, Dialysis, and Renal Transplantation Department, University North Hospital, Saint Etienne, France
| | - Francois Berthoux
- Nephrology, Dialysis, and Renal Transplantation Department, University North Hospital, Saint Etienne, France
| | | | - Evangeline Pillebout
- Center for Research on Inflammation, University of Paris, INSERM and CNRS, Paris, France
| | - Renato Monteiro
- Center for Research on Inflammation, University of Paris, INSERM and CNRS, Paris, France
| | - Raoul Nelson
- Division of Pediatric Nephrology, Department of Pediatrics, University of Utah, Salt Lake City, UT, USA
| | - Robert J Wyatt
- Division of Pediatric Nephrology, University of Tennessee Health Sciences Center, Memphis, TN, USA
- Children's Foundation Research Center, Le Bonheur Children's Hospital, Memphis, TN, USA
| | - William Smoyer
- Division of Pediatric Nephrology, Nationwide Children's Hospital, Columbus, OH, USA
| | - John Mahan
- Division of Pediatric Nephrology, Nationwide Children's Hospital, Columbus, OH, USA
| | - Al-Akash Samhar
- Division of Pediatric Nephrology, Driscoll Children's Hospital, Corpus Christi, TX, USA
| | - Guillermo Hidalgo
- Division of Pediatric Nephrology, Department of Pediatrics, HMH Hackensack University Medical Center, Hackensack, NJ, USA
| | - Alejandro Quiroga
- Division of Pediatric Nephrology, Helen DeVos Children's Hospital, Grand Rapids, MI, USA
| | - Patricia Weng
- Division of Pediatric Nephrology, Mattel Children's Hospital, Los Angeles, CA, USA
| | - Raji Sreedharan
- Division of Pediatric Nephrology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - David Selewski
- Division of Pediatric Nephrology, Mott Children's Hospital, Ann Arbor, MI, USA
| | - Keefe Davis
- Division of Pediatric Nephrology, Department of Pediatrics, The Medical University of South Carolina (MUSC), Charleston, SC, USA
| | - Mahmoud Kallash
- Division of Pediatric Nephrology, SUNY Buffalo, Buffalo, NY, USA
| | - Tetyana L Vasylyeva
- Division of Pediatric Nephrology, Department of Pediatrics, Nationwide Children's Hospital, Columbus, OH, USA
| | - Michelle Rheault
- Division of Pediatric Nephrology, University of Minnesota, Minneapolis, MN, USA
| | - Aftab Chishti
- Division of Pediatric Nephrology, University of Kentucky, Lexington, KY, USA
| | - Daniel Ranch
- Division of Pediatric Nephrology, Department of Pediatrics, University of Kentucky, Lexington, KY, USA
| | - Scott E Wenderfer
- Division of Pediatric Nephrology, Baylor College of Medicine/Texas Children's Hospital, Houston, TX, USA
| | - Dmitry Samsonov
- Division of Pediatric Nephrology, Boston Children's Hospital, Boston, MA, USA
| | - Donna J Claes
- Division of Pediatric Nephrology, Department of Pediatrics, New York Medical College, New York City, NY, USA
| | - Oleh Akchurin
- Division of Pediatric Nephrology, Department of Pediatrics, Weill Cornell Medical College, New York City, NY, USA
| | | | - Maria Stangou
- The Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Judit Nagy
- 2nd Department of Internal Medicine, Nephrological and Diabetological Center, University of Pécs, Pécs, Hungary
| | - Tibor Kovacs
- 2nd Department of Internal Medicine, Nephrological and Diabetological Center, University of Pécs, Pécs, Hungary
| | - Enrico Fiaccadori
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Antonio Amoroso
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Cristina Barlassina
- Renal Division, Dipartimento di Medicina, Chirurgia e Odontoiatria, San Paolo Hospital, School of Medicine, University of Milan, Milan, Italy
| | - Daniele Cusi
- Renal Division, Dipartimento di Medicina, Chirurgia e Odontoiatria, San Paolo Hospital, School of Medicine, University of Milan, Milan, Italy
| | | | | | | | - Emanuela Boer
- Division of Nephrology and Dialysis, Gorizia Hospital, Gorizia, Italy
| | - Luisa Bono
- Nephrology and Dialysis, A.R.N.A.S. Civico and Benfratelli, Palermo, Italy
| | - Giuliano Boscutti
- Nephrology, Dialysis and Renal Transplant Unit, S. Maria della Misericordia Hospital, ASUFC, Udine, Italy
| | - Gianluca Caridi
- Division of Nephrology, Dialysis and Transplantation, IRCCS Giannina Gaslini Institute, Genova, Italy
| | - Francesca Lugani
- Division of Nephrology, Dialysis and Transplantation, IRCCS Giannina Gaslini Institute, Genova, Italy
| | - GianMarco Ghiggeri
- Division of Nephrology, Dialysis and Transplantation, IRCCS Giannina Gaslini Institute, Genova, Italy
| | - Rosanna Coppo
- Regina Margherita Children's Hospital, Torino, Italy
| | - Licia Peruzzi
- Regina Margherita Children's Hospital, Torino, Italy
| | | | | | | | | | - Giovanni Frasca
- Division of Nephrology, Dialysis and Renal Transplantation, Riuniti Hospital, Ancona, Italy
| | | | - Maurizio Garozzo
- Unità Operativa di Nefrologia e Dialisi, Ospedale di Acireale, Acireale, Italy
| | - Adele Mitrotti
- Nephrology, Dialysis and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy
| | - Loreto Gesualdo
- Nephrology, Dialysis and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy
| | - Simona Granata
- Renal Unit, Department of Medicine, University of Verona, Verona, Italy
| | - Gianluigi Zaza
- Renal Unit, Department of Medicine, University of Verona, Verona, Italy
| | | | - Riccardo Magistroni
- Department of Surgical, Medical, Dental, Oncologic and Regenerative Medicine, University of Modena and Reggio Emilia, Modena, Italy
| | - Isabella Pisani
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Andrea Magnano
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | | | - Piergiorgio Messa
- Nephrology Dialysis and Kidney Transplant Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Università degli Studi di Milano, Milan, Italy
| | - Renzo Mignani
- Azienda Unità Sanitaria Locale Rimini, Rimini, Italy
| | - Antonello Pani
- Department of Nephrology and Dialysis, G. Brotzu Hospital, Cagliari, Italy
| | | | - Dario Roccatello
- Nephrology and Dialysis Unit, G. Bosco Hub Hospital (ERK-net Member) and University of Torino, Torino, Italy
| | - Maurizio Salvadori
- Division of Nephrology and Renal Transplantation, Carreggi Hospital, Florence, Italy
| | - Erica Salvi
- Renal Division, DMCO (Dipartimento di Medicina, Chirurgia e Odontoiatria), San Paolo Hospital, School of Medicine, University of Milan, Milan, Italy
| | - Domenico Santoro
- Unit of Nephrology and Dialysis, AOU G Martino, University of Messina, Messina, Italy
| | - Guido Gembillo
- Unit of Nephrology and Dialysis, AOU G Martino, University of Messina, Messina, Italy
| | - Silvana Savoldi
- Unit of Nephrology and Dialysis, ASL TO4-Consultorio Cirié, Turin, Italy
| | | | | | - Claudia Izzi
- Department of Medical and Surgical Specialties and Nephrology Unit, University of Brescia-ASST Spedali Civili, Brescia, Italy
| | - Federico Alberici
- Department of Medical and Surgical Specialties and Nephrology Unit, University of Brescia-ASST Spedali Civili, Brescia, Italy
| | - Elisa Delbarba
- Department of Medical and Surgical Specialties and Nephrology Unit, University of Brescia-ASST Spedali Civili, Brescia, Italy
| | - Michał Florczak
- Department of Immunology, Transplantology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland
| | - Natalia Krata
- Department of Immunology, Transplantology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland
| | - Krzysztof Mucha
- Department of Immunology, Transplantology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
| | - Leszek Pączek
- Department of Immunology, Transplantology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
| | - Stanisław Niemczyk
- Department of Internal Disease, Nephrology and Dialysotherapy, Military Institute of Medicine, Warsaw, Poland
| | - Barbara Moszczuk
- Department of Immunology, Transplantology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland
- Department of Clinical Immunology, Medical University of Warsaw, Warsaw, Poland
| | | | | | | | - Teresa Bączkowska
- Department of Transplantation Medicine, Nephrology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland
| | - Magdalena Durlik
- Department of Transplantation Medicine, Nephrology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland
| | - Krzysztof Pawlaczyk
- Department of Nephrology, Transplantology and Internal Medicine, Poznan Medical University, Poznan, Poland
| | - Przemyslaw Sikora
- Department of Pediatric Nephrology, Medical University of Lublin, Lublin, Poland
| | - Marcin Zaniew
- Department of Pediatrics, University of Zielona Góra, Zielona Góra, Poland
| | - Dorota Kaminska
- Clinical Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Magdalena Krajewska
- Clinical Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Izabella Kuzmiuk-Glembin
- Department of Nephrology, Transplantology and Internal Diseases, Medical University of Gdansk, Gdansk, Poland
| | - Zbigniew Heleniak
- Department of Nephrology, Transplantology and Internal Diseases, Medical University of Gdansk, Gdansk, Poland
| | - Barbara Bullo-Piontecka
- Department of Nephrology, Transplantology and Internal Diseases, Medical University of Gdansk, Gdansk, Poland
| | - Tomasz Liberek
- Department of Nephrology, Transplantology and Internal Diseases, Medical University of Gdansk, Gdansk, Poland
| | - Alicja Dębska-Slizien
- Department of Nephrology, Transplantology and Internal Diseases, Medical University of Gdansk, Gdansk, Poland
| | - Tomasz Hryszko
- 2nd Department of Nephrology and Hypertension with Dialysis Unit, Medical University of Bialystok, Bialystok, Poland
| | | | - Monika Miklaszewska
- Department of Pediatric Nephrology and Hypertension, Jagiellonian University Medical College, Krakow, Poland
| | - Maria Szczepańska
- Department of Pediatrics, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, Katowice, Poland
| | - Katarzyna Dyga
- Department of Pediatrics, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, Katowice, Poland
| | - Edyta Machura
- Department of Pediatrics, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, Katowice, Poland
| | - Katarzyna Siniewicz-Luzeńczyk
- Department of Pediatrics, Immunology and Nephrology, Polish Mother's Memorial Hospital Research Institute, Lodz, Poland
| | - Monika Pawlak-Bratkowska
- Department of Pediatrics, Immunology and Nephrology, Polish Mother's Memorial Hospital Research Institute, Lodz, Poland
| | - Marcin Tkaczyk
- Department of Pediatrics, Immunology and Nephrology, Polish Mother's Memorial Hospital Research Institute, Lodz, Poland
| | - Dariusz Runowski
- Department of Nephrology, Kidney Transplantation and Hypertension, Children's Memorial Health Institute, Warsaw, Poland
| | - Norbert Kwella
- Department of Nephrology, Hypertension and Internal Medicine, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - Dorota Drożdż
- Department of Pediatric Nephrology and Hypertension, Jagiellonian University Medical College, Krakow, Poland
| | - Ireneusz Habura
- Department of Nephrology, Karol Marcinkowski Hospital, Zielona Góra, Poland
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Larisa Prikhodina
- Division of Inherited and Acquired Kidney Diseases, Veltischev Research and Clinical Institute for Pediatrics of the Pirogov Russian National Research Medical University, Moscow, Russia
| | - David van Heel
- Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Bertrand Fontaine
- Sorbonne University, INSERM, Center of Research in Myology, Institute of Myology, University Hospital Pitie-Salpetriere, Paris, France
- Assistance Publique-Hôpitaux de Paris (AP-HP), Service of Neuro-Myology, University Hospital Pitie-Salpetriere, Paris, France
| | - Chris Cotsapas
- Departments of Neurology and Genetics, Yale University, New Haven, CT, USA
| | | | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Vito Annese
- CBP American Hospital, Dubai, United Arab Emirates
| | - Peter K Gregersen
- Robert S. Boas Center for Genomics and Human Genetics, Feinstein Institutes for Medical Research, North Shore LIJ Health System, New York City, NY, USA
| | | | - Matthew Weirauch
- Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Leah Kottyan
- Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - John B Harley
- US Department of Veterans Affairs Medical Center and Cincinnati Education and Research for Veterans Foundation, Cincinnati, OH, USA
| | - Hitoshi Suzuki
- Department of Nephrology, Juntendo University Faculty of Medicine, Tokyo, Japan
| | - Ichiei Narita
- Division of Clinical Nephrology and Rheumatology, Kidney Research Center, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Shin Goto
- Division of Clinical Nephrology and Rheumatology, Kidney Research Center, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Hajeong Lee
- Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dong Ki Kim
- Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yon Su Kim
- Biomedical Science, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jin-Ho Park
- Department of Family Medicine, Seoul National University College of Medicine and Seoul National University Hospital, Seoul, Republic of Korea
| | - BeLong Cho
- Department of Family Medicine, Seoul National University College of Medicine and Seoul National University Hospital, Seoul, Republic of Korea
- Institute on Aging, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Murim Choi
- Biomedical Science, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ans Van Wijk
- Amsterdam University Medical Centre, VU University Medical Center (VUMC), Amsterdam, the Netherlands
| | - Ana Huerta
- Hospital Universitario Puerta del Hierro Majadahonda, REDINREN, IISCIII, Madrid, Spain
| | - Elisabet Ars
- Molecular Biology Laboratory and Nephrology Department, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau, Universitat Autònoma de Barcelona, REDINREN, IISCIII, Barcelona, Spain
| | - Jose Ballarin
- Molecular Biology Laboratory and Nephrology Department, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau, Universitat Autònoma de Barcelona, REDINREN, IISCIII, Barcelona, Spain
| | - Sigrid Lundberg
- Department of Nephrology, Danderyd University Hospital, and Department of Clinical Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Bruno Vogt
- Department of Nephrology and Hypertension, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Laila-Yasmin Mani
- Department of Nephrology and Hypertension, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Yasar Caliskan
- Division of Nephrology, Saint Louis University, Saint Louis, MO, USA
| | - Jonathan Barratt
- John Walls Renal Unit, University Hospitals of Leicester, Leicester, UK
| | | | | | - Daniel P Gale
- Department of Renal Medicine, University College London, London, UK
| | | | - Thomas Rauen
- Division of Nephrology and Clinical Immunology, RWTH Aachen University, Aachen, Germany
| | - Jürgen Floege
- Division of Nephrology and Clinical Immunology, RWTH Aachen University, Aachen, Germany
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Arif B Ekici
- Institute of Human Genetics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Nan Chen
- Department of Nephrology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jingyuan Xie
- Department of Nephrology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Richard P Lifton
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Laboratory of Human Genetics and Genomics, The Rockefeller University, New York City, NY, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Department of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Eimear E Kenny
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
- Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York City, NY, USA
- Center for Population Genomic Health, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Iuliana Ionita-Laza
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York City, NY, USA
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Bruce A Julian
- Departments of Microbiology and Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jan Novak
- Departments of Microbiology and Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Francesco Scolari
- Department of Medical and Surgical Specialties and Nephrology Unit, University of Brescia-ASST Spedali Civili, Brescia, Italy
| | - Hong Zhang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
| | - Ali G Gharavi
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA.
- Institute for Genomic Medicine, Columbia University, New York City, NY, USA.
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198
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Kamal A, Arnold C, Claringbould A, Moussa R, Servaas NH, Kholmatov M, Daga N, Nogina D, Mueller‐Dott S, Reyes‐Palomares A, Palla G, Sigalova O, Bunina D, Pabst C, Zaugg JB. GRaNIE and GRaNPA: inference and evaluation of enhancer-mediated gene regulatory networks. Mol Syst Biol 2023; 19:e11627. [PMID: 37073532 PMCID: PMC10258561 DOI: 10.15252/msb.202311627] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/01/2023] [Accepted: 04/03/2023] [Indexed: 04/20/2023] Open
Abstract
Enhancers play a vital role in gene regulation and are critical in mediating the impact of noncoding genetic variants associated with complex traits. Enhancer activity is a cell-type-specific process regulated by transcription factors (TFs), epigenetic mechanisms and genetic variants. Despite the strong mechanistic link between TFs and enhancers, we currently lack a framework for jointly analysing them in cell-type-specific gene regulatory networks (GRN). Equally important, we lack an unbiased way of assessing the biological significance of inferred GRNs since no complete ground truth exists. To address these gaps, we present GRaNIE (Gene Regulatory Network Inference including Enhancers) and GRaNPA (Gene Regulatory Network Performance Analysis). GRaNIE (https://git.embl.de/grp-zaugg/GRaNIE) builds enhancer-mediated GRNs based on covariation of chromatin accessibility and RNA-seq across samples (e.g. individuals), while GRaNPA (https://git.embl.de/grp-zaugg/GRaNPA) assesses the performance of GRNs for predicting cell-type-specific differential expression. We demonstrate their power by investigating gene regulatory mechanisms underlying the response of macrophages to infection, cancer and common genetic traits including autoimmune diseases. Finally, our methods identify the TF PURA as a putative regulator of pro-inflammatory macrophage polarisation.
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Affiliation(s)
- Aryan Kamal
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
- Faculty of BiosciencesCollaboration for Joint PhD Degree between EMBL and Heidelberg UniversityHeidelbergGermany
| | - Christian Arnold
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
| | - Annique Claringbould
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
| | - Rim Moussa
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
| | - Nila H Servaas
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
| | - Maksim Kholmatov
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
| | - Neha Daga
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
| | - Daria Nogina
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
| | - Sophia Mueller‐Dott
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
| | - Armando Reyes‐Palomares
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
- Present address:
Department of Biochemistry and Molecular BiologyComplutense University of MadridMadridSpain
| | - Giovanni Palla
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
- Present address:
Institute of Computational BiologyHelmholtz Center MunichOberschleißheimGermany
| | - Olga Sigalova
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
- Faculty of BiosciencesCollaboration for Joint PhD Degree between EMBL and Heidelberg UniversityHeidelbergGermany
| | - Daria Bunina
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
| | - Caroline Pabst
- Department of Medicine V, Hematology, Oncology and RheumatologyUniversity Hospital HeidelbergHeidelbergGermany
- Molecular Medicine Partnership UnitUniversity of HeidelbergHeidelbergGermany
| | - Judith B Zaugg
- European Molecular Biology Laboratory, Structural and Computational Biology UnitHeidelbergGermany
- Molecular Medicine Partnership UnitUniversity of HeidelbergHeidelbergGermany
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199
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Liu Z, Chen Y, Xia Q, Liu M, Xu H, Chi Y, Deng Y, Xing D. Linking genome structures to functions by simultaneous single-cell Hi-C and RNA-seq. Science 2023; 380:1070-1076. [PMID: 37289875 DOI: 10.1126/science.adg3797] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 05/07/2023] [Indexed: 06/10/2023]
Abstract
Much progress has been made recently in single-cell chromosome conformation capture technologies. However, a method that allows simultaneous profiling of chromatin architecture and gene expression has not been reported. Here, we developed an assay named "Hi-C and RNA-seq employed simultaneously" (HiRES) and performed it on thousands of single cells from developing mouse embryos. Single-cell three-dimensional genome structures, despite being heavily determined by the cell cycle and developmental stages, gradually diverged in a cell type-specific manner as development progressed. By comparing the pseudotemporal dynamics of chromatin interactions with gene expression, we found a widespread chromatin rewiring that occurred before transcription activation. Our results demonstrate that the establishment of specific chromatin interactions is tightly related to transcriptional control and cell functions during lineage specification.
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Affiliation(s)
- Zhiyuan Liu
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Yujie Chen
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Qimin Xia
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Menghan Liu
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Heming Xu
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Yi Chi
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Yujing Deng
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Dong Xing
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
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200
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Heer M, Giudice L, Mengoni C, Giugno R, Rico D. Esearch3D: propagating gene expression in chromatin networks to illuminate active enhancers. Nucleic Acids Res 2023; 51:e55. [PMID: 37021559 PMCID: PMC10250221 DOI: 10.1093/nar/gkad229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 03/06/2023] [Accepted: 04/03/2023] [Indexed: 04/07/2023] Open
Abstract
Most cell type-specific genes are regulated by the interaction of enhancers with their promoters. The identification of enhancers is not trivial as enhancers are diverse in their characteristics and dynamic in their interaction partners. We present Esearch3D, a new method that exploits network theory approaches to identify active enhancers. Our work is based on the fact that enhancers act as a source of regulatory information to increase the rate of transcription of their target genes and that the flow of this information is mediated by the folding of chromatin in the three-dimensional (3D) nuclear space between the enhancer and the target gene promoter. Esearch3D reverse engineers this flow of information to calculate the likelihood of enhancer activity in intergenic regions by propagating the transcription levels of genes across 3D genome networks. Regions predicted to have high enhancer activity are shown to be enriched in annotations indicative of enhancer activity. These include: enhancer-associated histone marks, bidirectional CAGE-seq, STARR-seq, P300, RNA polymerase II and expression quantitative trait loci (eQTLs). Esearch3D leverages the relationship between chromatin architecture and transcription, allowing the prediction of active enhancers and an understanding of the complex underpinnings of regulatory networks. The method is available at: https://github.com/InfOmics/Esearch3D and https://doi.org/10.5281/zenodo.7737123.
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Affiliation(s)
- Maninder Heer
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Luca Giudice
- Department of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Claudia Mengoni
- Department of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy
| | - Rosalba Giugno
- Department of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy
| | - Daniel Rico
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
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